1 Logic Programming based Internet Technologies 2000 International Summer School in Computational...

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Logic Programming based Internet Technologies

2000 International Summer School in Computational LogicAcquafredda di Maratea (Basilicata, Italy) September 3-8, 2000

Copyright © 2000, Paul Tarau

Paul TarauUniversity of North Texas

&BinNet Corporation

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Logic Programming based Internet Technologies

Paul TarauPaul Tarau

[email protected]@cs.unt.edu

http://www.cs.unt.edu/~tarauhttp://www.cs.unt.edu/~tarau

http://www.binnetcorp.comhttp://www.binnetcorp.com

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PART I: An Overview of Internet Development Trends

• A Goal Oriented view:

– WHY to develop for the Internet?

– WHAT to develop for the Internet?

– HOW to develop for the Internet?

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Internet Growth: driven by E-Commerce

• Critical mass needed: ~20% online

• from random graphs: sudden emergence of a big component

• Growth of E-commerce (US)1998 -> $29 billion1999 -> $98.4 billion2003 -> $1.2 trillion (source: eMarketer)

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Buying over the Internet

• Initial markets: software, travel, books, CDs - MP3

• online stock trading: Schwab, E-Trade, Suretrade

• online grocery: back to the future:-) HomeGrocer, NetGrocer

• online drugstores, cars, jobs, entertainment, etc.

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Auctioning systems/electronic markets

• eBay, priceline

• price comparison/item matching agents:

– EBay's Personal Shopper

– Amazon’s book recommandations

• more conventional shopping chart?

• refereal programs: Amazon, priceline

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Trends in E-Commerce

• Integration of e-commerce and corporate data processing systems– backend databases: DB2, Oracle

• Complete e-commerce solutions vs. component based e-commerce systems– complete solution offerings: IBM– CGI scripts (Perl), servlets, SSI, Active

Server Processes (ASP), Java based JSP

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Internet based e-commerce infrastructure

• WWW - still in exponential growth for the next few years

• payment is just Information Exhange - subject to automation!

• Shopping by features: search, online browsing can do it better than asking a (not always) knowledgeable salesperson

• place for LP/CP: the need for intelligent knowledge processing

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Encryption, digital signatures

• conventional cryptography: DES, BlueFish• public key cryptography: RSA, PGP• confidentiality: PGP only a given group can

decode, no need for key exchange• authentication

– digital signature, certificates - VeriSign etc. – new US law – Fall 2000 !!!

• virgin territory for LP/CP: cryptography! Code breaking: a CLP problem !!!

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Secure transactions

• SSL basic security built in most browsers, alternative: SHTTP– still much better than conventional paper

based security

• DES: is it good for business transactions? (40 bit ok, 128bit - truly secure)

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Forms of electronic payment

• Electronic Money

– anonymus, unforgeable, “sound” - a place for LL?

• smart cards - downloadable from online account

• is third party certification needed?

• E-checks vs. credit cards vs. e-cash

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Predictions/Trends?

• E-commerce will completely reshape financial institutions

• it is likely to replace various forms of catalog and mail order businesses

• successful in information based (books, CDs), high margin/low volume, expensive to keep in inventory products, B2B

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Search Engines, Portals, Service Sites

• Trend: from Information to Knowledge - a place for LP/CP

• Search engines: Google, AltaVista, Snap, AskJeves - NL

• Portals: Yahoo, Lycos• Specialized service sites:

– books: www.amazon.com– travel: www.travelocity.com

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Complete Knowledge Management Solutions

• http://www.excalib.com/ RetrivalWare, Internet Spider, WebExpress

• Intelligent search, knowledge management

• Very highly priced complete solutions:

– Document management, paperless office, multiple formats, intranet/Internet search

– A chance for LP: Prolog as SuperPerl !!!

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Typical Features of KM tools - WebExpress 2.0

• SGML, XML and meta-tag support

• Multiple language plug-in architecture

• High-level Java API customization

• Support for over 200 data types, including popular web formats such as HTML and PDF

• Easy LP link: Jinni 2000 – all in Java

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File Sharing Communities

• NAPSTER - virus-like sharing: downloads become automatically uploadable

• Gnutella - no central server - GNU license

• MP3.com => Rio Player -> Sony?

• complex legal issues - piracy vs. legitimate sharing - similar to giving a CD to a friend?

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Basics of Internet Infrastructure: TCP/IP

• packet switching vs. dedicated point-to-point link

• Post Office (small packets ) vs. Phone Center (point-to-point link)

• IP header: address 129.120.44.123 vs.

• domain based naming: www.cs.unt.edu

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Static vs. Dynamic IP addresses

• self contained server and web site: static IP

• connecting through an ISP: dynamic IP:-(

– in fact, this comes from running out of available IP addresses - upcoming extended IP numbers might solve this - it is quite humiliating for users to be: cust007.my_isp.com instead of being www.JamesBond.com :-)

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How to create and register a new domain?

• www.internic.net: (not a NSI monopoly anymore!)

• new agency: http://www.icann.org/

• http://www.networksolutions.com/

• Whois service: http://www.nsiregistry.com/

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How to create a Web Site?

• Dedicated server – static IP, domain name– T1 (large volume, high cost) or ISDN

(metered, slow, starts to look outdated)– new: DSL: ADSL vs. SDSL)– What OS? Linux+Apache (more flexible)

NT (compatible with other MSoft tools)• Through Web hosting (inexpensive and

reliable but less flexible)

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Hypertext Markup Language (HTML) basics

• <HTML>

• <HEAD>

• <TITLE> Welcome To My Page </TITLE>

• </HEAD> <BODY>

– other html code

• </BODY>

• </HTML>

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Adding Links

• <A HREF=

• “http://www.mycompany.com”>

• My Company

• </A>

• In the Web page it looks like this:

– … My Company …

• <A HREF="mailto:[email protected]">my email</A>

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Including Images and Sound

• <IMG SRC=pictures/me_and_my_dog.gif>

• good compression: JPG

• animated GIFs - easy to make - size can be a problem

• Sound: MID (small) WAV, AU (older formats) MP3 (high quality)

• static (tag: EMBED, BGSOUND) vs. streaming audio/video: RealAudio

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Including CGI scripts

• <form method="post”

• action="http://a.b.c.d/cgi-bin/myscript.exe?query=who" >>

• <input type="submit" size="40" value="Search">

• </form>

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Including Java Applets

• <applet

• code=”myapplet.class"

• height="200" width="600” >

– <param

• value=”999”

• name=”default_price" >

• </applet>

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Tools for Building Web Sites

• HTML, tables, forms, CGI scripts

• server side tools: SSI, ASP, servlets

• Media formats: GIF, JPEG, MPEG, real audio

• Executable content: Java

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Design tools

• Composer, Microsoft Word, FrontPage

– Generating HTML

• Generating Java applets: Symantec, J++ 6.0

• Generating 3D content: VR Creator, TrueSpace

• LP/CLP tools need to interoperate with them!

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Alternative Content Formats

• VRML - now supported also by Java3D

– has links like in HTML

– has superior navigation

– has higher information density

• The future is 3D - the Nintendo generation grows up:-)

• LP/CLP tools should interoperate with the emerging 3D Web

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Conclusion of PART I

• LP/CLP comes late into the Internet Business

• it should get into fast growing or still emerging areas– e-commerce, B2B, KM, vertical markets– intelligent search, knowledge processing,

agents– 3D Web, new Internet infrastructure

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Basic Internet Programming

see also online demos at:

• http://www.binnetcorp.com

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CGI Scripts - BinProlog: counter

main:-header,inc(X),show_counter(X).

header:- write('220 ok'),nl, write('content-type: text/html'),nl,nl.

show_counter(X):-write(counter(X)),write('.'),nl.

inc(X):- F='cstate.pro', ( see_or_fail(F)-> see(F),read(counter(X)),seen ; X=0 ),X1 is X+1, tell(F),show_counter(X1),told.

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Installing a CGI Script

• Put the bp executable+script in a directory like cgi-bin

• Call it from a HTML page as follows:

<TITLE> BinProlog CGI counter</TITLE><HTML><BODY>Try a BinProlog based<A HREF= "/bp_inet/bin/bp.exe?$/bp_inet/cgi/counter.pro"> CGI Web-counter! </A> </BODY></HTML>

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A BinProlog Query Evaluator

• A more complex script (see files cgi/query.pro and cgi/query.html) needs to be used to pass information from a HTML file to the Prolog script.

• BinProlog's cgi_lib.pro library uses POST method for sending information to the server.

• This means, that after some basic header exchange, the client will read and parse from the standard input field names/field data pairs.

• This is achieved by components in cgi_lib.pro, the script itself matches the expected parameters and proceeds with its specific tasks.

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CGI script for querying BinProlog over the net

:-['../library/cgi_lib'].

:-['../library/http_tools'].

main:-run_cgi(5,body).

% POST method body

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CGI query script - continued

body:-

(get_cgi_input(Alist)->true;test,fail),

Alist = [

login=Ls, passwd=Ps,email=Ms,

home=Hs,query=Qs,editor=Es

]

->

( run_it(Ls,Ps,Ms,Hs,Qs,Es)->true

; write('Error in query: '),write_chars(Qs),nl

)

; ( write('Non matching fields in form'),fail ; nl).

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BinNet HTTP Client

• reconsult_url(AtomicURL): reconsults a Prolog file from a Web server i.e. replaces each predicate with a new definition found there, asserted to the current database

• http2line(AtomicURL,Line): Opens a URL, then gets a stream of lines of chars from the WWW server. It will backtrack over them.

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URL example:

AtomicURL='http://…/test.txt’ pointing to the a file containing the lines:

This

is

a test.

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URLs as files -how it works?

?- http2line('http://…/test.txt',Line).

....

.... % some header lines

....

Line=[84,104,105,115];

Line=[105,115];

Line=[97,32,116,101,115,116,46];

no

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VRML in Prolog: a Case Study in Classic Internet Programming

• a Prolog to VRML mapping allowing generation of dynamic VRML pages through CGI and server side Prolog scripts – Assumption Grammars are used to mimic VRML

syntax and semantics – integrated knowledge processing and 3D data

visualization applications – self-contained BinProlog application: Web Server,

Data Extraction module and an Assumption Grammar based VRML generator

– Web programming: a simple CGI-script

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Motivation

• Internet programming: a richer infrastructure than HTML based "flat" WWW

• Goal: `intelligent' agent programming in multi-user Virtual Worlds (VRML'97, Java3D, synchronized worlds) unified and scalable framework for coordination, remote execution, Web connectivity, remote execution mechanisms, mobile code

• Virtual Worlds: Social computing in a visual (3D, VRML 2.0, animated) framework

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Overview of VRML

• the VRML scene is composed of nodes and routes • scalings, rotations and translations => transform nodes

(may be nested) • sensors

associated with geometry for sensing time interpolator nodes: keys => keyValues

• sensors can respond to: proximity to an avatar, mouse clicks/movement

• events are propagated with ROUTE statements between chained nodes

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VRML and Prolog: why?

• hierarchical space representation + event propagation for animation = VRML'97

• declarative SPACE representation and TRUTH representation share the same difficulties w.r.t TIME and change

• Prolog+VRML synergy: knowledge processing, inference <=> 3D visualization, animation, Internet

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Assumption Grammars

• AGs: multi-stream DCGs with implicit arguments and temporary assertions, scoping over the current AND-continuation

• Assumed code, intuitionistic and linear implication Clause=>Goal or [File]=>Goal ?- *a(13),-a(X),-a(Y)

• succeeds: (13) matches both a(X) and a(Y).Clause-:Goal or [File]-:Goal ?- +a(13),-a(X),-a(Y).fails: a(13) is usable only once!

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The Assumption Grammar API

*A and A=>B: add intuitionistic assumption A+A and A-:B: add linear assumption A-A: matches an assumption in curr. scope or fails#<Tokens : initializes/unifies the DCG stream#Token: matches or inserts a Token#>State: returns the current State?- #<[a,b,c,d],#A,#B,#>LeftOver.A=a, B=b,LeftOver=[c,d]?- #<Xs,#a,#b,#c,#>[].Xs=[a,b,c]

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Why AGs?

• The combination of DCG stream operations and assumptions is particularly well suited for generating hierarchical data structureswhere properties hold for selected subobjects.

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A syntactical mapping: VRML is Prolog

• VRML: hierarchical decomposition of the space in regions

• Prolog: terms as trees• concrete syntax: arguments are named, not

positional • VRML 2.0 ROUTES are structurally similar

to DCGs:• they are used to thread together streams of

change

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Pseudo VRML in Prolog: a PROTO

proto anAppearance @[ exposedField('SFColor')=color(1,0,0), exposedField('MFString')=texture@[]] @{ 'Appearance' @{ material='Material' @{ diffuseColor is color }, texture='ImageTexture' @{ url is texture }}}.

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How it looks in VRML?

VRML V2.0 utf8 PROTO anAppearance [ exposedField SFColor color 1 0 0 , exposedField MFString texture [] ] { Appearance { material Material { diffuseColor IS color } texture ImageTexture {url IS texture} } }

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Some Prolog Macros

shape(Geometry):- % based on scoped assumptions (=>) default_color(Color), toVrml( aShape @{ geometry(Geometry@{}), Color }

).

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Simple Shapes

sphere:- shape('Sphere').

cone:- shape('Cone').

cylinder:- shape('Cylinder').

box:- shape('Box').

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Using Prolog macros

group @{ children @[ `transform( translation(0,10,4),scale(2,2,2), rotation(0,0,0,0), [`sphere, `cone] ), `transform( translation(5,0,0),scale(1,3,6), rotation(0,1,0,1.5), [`box])]}.

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Using assumptions in the VRML generator macros

using a scoped implication to color blue a complete sub-object (cone) expressed itself as a macro:

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Saucer

def saucer = `transform( translation(0,1,1),scale(0.6,0.2,0.6), rotation(0.5,0.5,0,1.5), [ `sphere, % propagates a color over a region `(color(blue)=>>cone) ])

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From the Translator: (with Assumption Grammars)

toVrml(X):-number(X),!,#X.

toVrml(X):-atomic(X),!,#X.

toVrml(A@B):-!,#indent(=), toVrml(A), toVrml(B).

toVrml(A=B):-!,toVrml(A), toVrml(B).

toVrml(A is B):-!,#indent(=), toVrml(A), #'IS', toVrml(B).

toVrml({X}):-!,#'{',#indent(+), toVrml(X), #indent(-),#'}'.

toVrml(`X):-!,X.

toVrml(X):-is_list(X),!,

#'[',#indent(+), vrml_list(X), #indent(-),#']'.

toVrml(X):-is_conj(X),!,vrml_conj(X).

toVrml(T):-compound(T), #indent(=), vrml_compound(T).

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What's generated?

Group { children [ Transform { translation 0 10 4 scale 2 2 2 rotation 0 0 0 0 children [ # aShape is a VRML 2.0 PROTO! aShape { geometry Sphere{} color 0.7 0.8 0.8} , aShape { geometry Cone{} color 0.6 0.3 0.9} ] } , ..... ] }

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CGI based generator

• Figure

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Using the CGI based Generator

• the user clicks on button or VRML anchor

• a CGI script is invoked by the HTTP server

• the BinProlog based VRML generator is activated

• the dynamic VRML page is sent back to the client

• the browser's VRML plugin displays the results

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Server Side GeneratorFigure

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Using the Server Side Generator

Generator embedded in a Prolog server: • the user clicks on a button in a HTML form or on

VRML anchor • the VRML generator working as a server side

Prolog thread is activated• the dynamic VRML page is sent back to the client• the browser's VRML plugin displays the results

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Server + Web Agents

• Figure

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Prolog HTTP Server With VRML Generator, Web Data

Extraction and Persistent State

• multi-agent architecture

• multi-threaded Prolog engine

• blackboard constraints

• Linda coordination

• VRML/Java3D based visualization agents

• Prolog based reasoning agents

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Some cross-fertilization opportunities:

• Prolog is a great VRML syntax checker! • Prolog as a powerful macro language/static optimizer for

VRML• Prolog as an AI planner for complex intelligent avatar

movement in VRML• Prolog as a scripting language: TERMS represent well

trees of 3D object groupings! • completely powerless: Javascript • unnecessarily complex: Java+EAI

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MUDs, MOOs and Virtual Worlds

• traditionally direct phone links connect to MUDs, MOOs using telnet for chat and game playing - the Internet itself - a giant MUD?

• The standard container object is called a room

• People can move around the rooms in the virtual world and interact with other users

• MUDs come with a programming language that the users can use to program the behavior of objects in the environment

• User extensibility: a MUDs allow creation of new rooms and new objects, and to define their behaviors

• Virtual Worlds: MOOs in a visual (3D, VRML 2.0, animated) framework

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The LogiMOO project:

• a toolkit for creating Prolog based virtual worlds for distributed group-work over the Internet

• embedded in Netscape or Explorer

• NL interface: `controlled english'

• LogiMOO: unification for pattern retrieval - exclusively deterministic operations, unlike most Prolog based Linda systems

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Related work

ILPS'97 LP and Internet Tutorial

WWW and LP/CLP languages: M. Hermenegildo, M. Caro, G. Pueblo (the Madrid group)

they also did visualisation of program execution traces main difference: the ability to use assumptions to parameterize deep components of VRML trees a code transformer needs to be written to replace cylinders by cones in the Prolog sources of a VRML page we can expand a generic macro shape and then pass the actual value (cone or cylinder) as an intuitionistic assumption, when themacro is called, the effect of the assumption will generate either

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Conclusion PART II

• Prolog as a program generator for special purpose languages without processing abilities like VRML

• syntax-mapping: reuse of VRML programming skills

• Web based architectures for generating dynamic VRML, persistent server side state and multi-user synchronization

• Prolog can be used as a macro language for building compact template files

• typical AI components like Prolog planners can be used for realistic avatar movement in VRML worlds

• interesting synergy between Prolog’s Internet data extraction ability and VRML's animated 3D visualization.

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PART III Internet and Network Programming with Jinni

• LP languages are OLD - Prolog is already 20++• We need to specialize LP languages, transform

them, adapt them, change them radically, if needed, e.g:– Reading from a URL should be as simple as

reading from a file– Interacting over a socket should be as simple as

interacting on a local console– Computations should be able to move across

the network transparently

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Why we need a pure Java based Logic Programming Language?

• LP needs to be specialized for high level networking, easy handling of URLs, client-server computations, execution of multiple “agent” threads, handling of various Internet protocols

• Transparent access to zillions of Java libraries – it just seems the most pragmatic way to provide main stream programming patterns to logic programmers

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Jinni 2000: fast Prolog in pure Java

• 1 million LIPS Java based Prolog• integrates Kernel Prolog with fast continuation

passing BinWAM engine• runs even on Palm, Handspring (with Sun’s new

Java engine: K-machine) palmtops • blackboards, threads, remote predicate calls• agents: generalization of class and object based

OO systems – local and remote delegation mechanism

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Jinni Ontology

• Places: blackboards + a server thread listening on a port

• Things: Prolog terms, in particular Prolog clauses• Agents:

– a set of mobile threads initiated by a unique goal at a given Place

– coordination: through blackboards - some local, some remote

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Orthogonal Execution Mechanisms

• engines (1MLips compiled or lightweight)• threads + hubs• remote predicate calls• derived: blackboard operations

– basic Linda coordination, associative search

– blackboard constraints - react when something becomes true

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Engines as Generalized Iterators (Fluents): keep state minimal

Engine = an LD Resolution Interpreter with first order control: constructor+iterator– new_engine(Goal,AnswerPattern, Handle):

creates a new interpreter Handle solving Goal– new_answer(Handle,AnswerInstance): If

AnswerInstance is no then stops the engine, otherwise either returns a new answer, of the form the(AnswerInstance) or returns no if there are no more answers.

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findall/3

findall(X,G,Xs):- new_engine(G,X,E), new_answer(E,Answer), collect_all_answers(Answer,E,Xs).

collect_all_answers(no,_,[]). collect_all_answers(the(X),E,[X|Xs]):-new_answer(E,Answer), collect_all_answers(Answer,E,Xs).

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Thread Operations: minimal!

• bg(Goal,ThreadHandle)

• hub_ms(Timout): syncs M producers N consumers

• thread_join(T)

• sleep_ms(Duration)

• current_thread(ThisThreadHandle)

• Derived: thread_resume/1, thread_suspend/1

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Remote Predicate Calls

• run_server(Port,Pwd):

• ask_server(X,GX,Pwd,Host,Port,Result)

• abstract transport layer

– unicast sockets

– RMI, Corba, multicast sockets

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Basic Linda Operations (now derived)

• out(X): puts X on the blackboard

• in(X): waits until it can take an object matching X from the blackboard

• all(X,Xs): reads the list Xs matching X currently on the blackboard

• derived operations: cin/1, rd/1

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Assertional Constraints vs. Binding Constrains

• From: when nonvar(X) ...

• => when provable(X) … re-execution

• => when a_fact(X)… more realistic

• constraints on variable bindings are too fine-grained for distributed programming!

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Beyond Linda: Blackboard Constraint Operations

• wait_for(Pattern,Constraint): waits for a Pattern on the blackboard, such that Constraint holds, and when this happens, it removes the result of the match from the blackboard

• notify_about(Pattern): notifies about this Pattern one of the blocked threads which waits for it with a matching constraint

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Coordination with Blackboard Constraints

• Two threads: T1 (prod) and T2 (cons)

• ?-notify_about(stock_offer(aol,91)). %T1

• ?-notify_about(stock_offer(aol,89)). %T1

• % action triggered in T2 => Price=89

• ?-wait_for(stock_offer(aol,Price), %T2 less(Price,90)).

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Mobile Threads: Motivation

– paradigm shift towards networked, mobile, ubiquitous computing with increasingly complex patterns of interaction

– threads: needed for programming reactive/proactive mobile agents

– back to pure LP - a good thing - but let’s give it an expressiveness lift:-)

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mobile threads: WHY?

• Large database, small agent

• Speed-up: move to a fast processor and back, transparently

• here/there switch: same code can be run locally or remotely

• fault tolerance - move->run->come back

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mobile threads with First Order AND-continuations

• a:-b,c,d.• binarization: a(C)::-b(c(d(C))).• get_cont(C,C)::-true(C). % binarized• mobile threads algorithm:

– move/0: get continuation, send over the net, resume execution on target

– return/0: send back new continuation, resume execution back home

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A Simple API for mobile threads (Jinni 98, BinProlog 7.x)

• run_server/0, here/0, there/0, where/1: => local or remote focus

• set_this_host/1, set_this_port/1, set_that_host/1,set_that_port/1

• move/0, return/0 vs. remote_run/1• the(Pattern,Goal,Answer): runs Goal to

produce the(Answer) or no => here/there switch =>local/remote

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mobile threads vs. RPCs: move once, compute many times

• ?-for(I,1,1000), remote_run(println(I)), eq(I,1000).

• ?-there, move, for(I,1,1000), println(I), eq(I,1000).

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Examples of mobile threads

• Window 1: a mobile thread

• ?- there, move, println(on_server), member(X,[1,2,3]), return, println(back).

• Window 2: a server

• ?- run_server.

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The (Pseudo) Server-in -the Client Pattern

• a client thread emulates server functionality (works behind a firewall!):– pseudo_sever:-

in(todo(X)),call(X),pseudo_server.– ?- there,pseudo_server.

• the real client: there,out(todo(…))• communication: through a blackboard on a

(shared) real server

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Shared Virtual Worlds

• set-up a registration mechanism for agents on server

• publish state changes to shared blackboard on server with out/1

• one thread for each “ghost” (remote client) - too expensive!

• => NEED FOR MULTICAST

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A Classic Design Pattern, Publish/Subscribe: with mobile

threads + Linda operations• a reactive channel listener: in/1 loop

• ?-listen(fun(_)).

• selective channel publisher: out/1 loop

• ?-talk(fun(jokes)).

• will not match:

• ?-talk(stocks(quotes,nasdaq))

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The (Pseudo) Server in The Client Pattern

• a client thread emulates server functionality (works behind a firewall!):– pseudo_sever:-

in(todo(X)),call(X),pseudo_server.– ?- there,pseudo_server.

• the real client: there,out(todo(…))• communication: through a blackboard on a

(shared) real server

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The Octopus Agent Pattern

• branch out multiple Reactive Agent threads to various places using RPCs or mobile threads

• watch for patterns containing returned results on the local blackboard

• failure or non-termination of one thread have minimal effect: fault tolerance

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Designing Jinni Agent Classes

• Java layer: – code and type inheritance– reaction to events– libraries: Java3D, XML, special devices etc.

• Prolog layer– knowledge processing– reaction to blackboard constraints– mobile threads

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Design Patterns in Visual Jinni

• drives Java objects through handles

• meta-programming is essential

• Java events interoperate with blackboard coordination

• easy extension to incorporate access to Java2D and Java3d libraries

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Java Objects in Visual Jinni

jdialog(Query,Answer):-

new_frame('Jinni Dialog',border,F),

new_label(F,Query,_),

new_panel(F,flow,P),

new_button(P,'Cancel', out(bc(P,cancel))),

new_button(P,'Ok',out(bc(P,ok))),show(F),

in(bc(P,Answer)),destroy(F).

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Shared Virtual Reality Agents

• Web based: browser+EAI+Java+Jinni

• Jinni Server + Thin Jinni Applet Connector

• BETTER: Java 3D virtual worlds connected in a peer-to-peer Jinni network

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Educational Agents

• chat, self organizing groups, shared VR

• alerts triggered by blackboard constraints

• reusable agent hierarchies

• Wizard of Oz help desk: combined human and programmed agents

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A Multicast Layer for Jinni

• Multicasting:In a network, a technique that allows data, including packets, to be simultaneously transmitted to a selected set of destinations (Some networks, such as Ethernet, support multicast by allowing a network interface to belong to one or more multicast groups).

• API– run_mul_server(Host, Port)– remote_mul_run(Host, Port, X, G, PW,

Res)

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Basic Linda Operations with Unicast and Multicast

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Impact on Mobile Computers and transient IP systems

– Server/Servant duality - pulling commands through multicast - applets as servers

– SETI-style distriuted computing– mobile agents for mobile devices

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Applications: Tele - Teaching

• LANs are Multicast Capable• Student machines join multicast group of teaching

server (run_mul_server)• Messages and todo tasks Multicasted to student

machines (remote_mul_run(out(todo(X)))• The server can collect responses from local

blackboards with expanded concept of blackboard remote_mul_run(mul_all(answer(X))

100

Dynamic Multicast based Tele-Teaching Chat

Work Done by Ravi Kiran Guntupalli

101

Dynamic Multicast based Performance Rater

Work Done by Ravi Kiran Guntupalli

102

Application: Java3d Games• API new_obj(name), move_obj(name,x,y,z), remove_obj(name)

• multicast - synchronization

• blackboard - preserve state.

• Prolog intelligent Logic Programming of agents

103

Future Work on Multicast Agents

• multicast: UDP based unreliable Protocol

• number of places attached unknown

• blocking reads unreliable

• experimentation with Reliable Multicast

• experimentation outside LANs i.e. with Routers capable of multicast

104

Conclusion of PART III

• Synergy between high performance networking and Prolog agents

• promising applications - networked AI games, tele-teaching, shared VR

106

Motivation

• uniform interface for controlling multiple interpreters and external stateful objects

• redesigning Prolog's system of built-in predicates: OO hierarchy (other Fluents)

• interoperation with the underlying Java system =>

• elegant integration of Internet Programming patterns

107

What’s wrong with Prolog’s builtins?

• LP => forever young!• old, deprecated builtins - early Fortran, C

inspired design - consolidated into “industrial strength” ISO standard :-)

• Zeppelins vs. air plains => the paradigm consolidation disease (do we have it?)

• messy flat function set => we need a modern, clean, compositional OO hierarchy

108

What’s wrong with Prolog’s reflection?

• call(X): control is not reflected properly - for instance backtracking is not a “first order” citizen

• basic things difficult: i.e. source level definition of exception handling

• general problem: lack of genericity (lists operations => conjunctions?)

109

What are Fluents?

• simple stateful entities - evolving through an abstract set of stepping operations

• Files, URLs, client/server interaction streams, GUI event streams

• Prolog interpreters (and runtime engines): just other Fluents!

• => a way to map linear recursion to fast iteration

110

Refactoring Prolog: a Fluent based design

• Kernel Prolog: a collection of Horn Clause Interpreters (Answer Sources) running LD-resolution on a given clause database and calling built-in operations

• a constructor: goal + answer pattern => answers can be explored one by one

• the Fluent encapsulating the state of the interpreter is very similar to a file or URL descriptor encapsulating the state of a Reader!

111

Fluent Classes

class Fluent extends SystemObject {Fluent(Prog p) {trailMe(p);}protected void trailMe(Prog p) {

if(null!=p) p.getTrail().push(this);

}public void stop() {}protected void undo() {stop();}

}

112

Source Fluents

abstract class Source extends Fluent {

Source(Prog p) {

super(p);

}

abstract public Term get();

}

113

Sink Fluents

abstract class Sink extends Fluent {

Sink(Prog p) {super(p);}

abstract public int put(Term T);

public Term collect() {

return null;

}

}

114

Fluent Composers I

• append_sources/3: creates a new Source with a get/2 operation such that when the first Source is stopped, iteration continues over the elements of the second Source.

• compose_sources/3: a cartesian product style composition, get/2 returnins pairs of elements of the first and second Source

• reverse_source/2 builds a new Source such that its get/2 returns in reverse order

115

Fluent Composers II

• split_source/3 creates two Source objects identical to the Source given as first argument - allows writing programs which iterate over a given Source multiple times

• join_sinks(S1,S2,S) creates a sink S such that its put operation go to both S1 and S2

• discharge(Source,Sink): sends all the elements of the Source to the given Sink

116

Fluent Modifiers

Fluent modifiers allow dynamically changing some attributes of a give Fluent

• set_persistent(Fluent,YesNo) is used to make a Fluent survive failure, by disabling its undo method, which, by default, applies the Fluent's stop method on backtracking

117

Interpreters (and run-time engines) as Fluents

Engine = LD Resolution Interpreter with first order control: constructor+iteratoranswer_source(+Goal, +AnswerPattern,

-Handle): creates a new interpreterget(+Handle, -AnswerInstance): returns a

new answer the(AnswerInstance) or no if no more answers

stop(+Handle): frees resources

118

Building some “built-ins”

% returns the(X) or no as first solution of G

first_solution(X,G,Answer):-

answer_source(X,G,Solver),

get(Solver,R),

stop(Solver),

eq(Answer,R).

119

once/1 and not/1

% binds G to its first solution or fails

once(G):-first_solution(G,G,the(G)).

% succeeds without binding G, if G fails

not(G):-first_solution(_,G,no).

120

Reflective Meta-Interpreters

% metacall/1: just reflects backtracking

% through element_of/2

metacall(Goal):-

answer_source(Goal,Goal,E),

element_of(E,Goal).

121

Reflecting backtracking

element_of(I,X):-

get(I,the(A)),

select_from(I,A,X).

select_from(_,A,A).

select_from(I,_,X):-

element_of(I,X).

122

Findall with Source Operations

findall(X,G,Xs):-

answer_source(X,G,Solver),

source_list(Solver,Xs).

123

Internet Related Fluents:

• URL and ZIP/JAR reader fluents

• => consult(‘http://…./progs/test.pl’)

• url2tokens(‘http://…/test.html’,Tokens).

• URL, file, database, socket fluents – look all the same – this also extends to local and remote Prolog interpreters

124

Conclusion of Part IV

• uniform interoperation of Horn Clause Solvers with stateful entities (Fluents)

• Integration of LP with external class libraries• a simplified Prolog built-in predicate system• => transparent handling of Internet objects and

protocols

125

Links to LP/CLP Web resources

• http://www.clip.dia.fi.upm.es/miscdocs/pillow/pillow.html

• http://www.cs.mu.oz.au/~swloke/logicweb.html

• http://www.cs.kuleuven.ac.be/~bmd/PrologInJava

• http://www.amzi.com, http://www.lpa.co.uk

• http://www.ifcomputer.com

• http://www.mozart-oz.org/

• http://www.binnetcorp.com

• http://www.cs.unt.edu/~tarau

126

LP & Web Tutorials

• Manuel Hermenegildo's tutorials:– http://www.clip.dia.fi.upm.es/lpnet/

pillow_sl_imperial/pillow_sl_imperial.html– http://www.clip.dia.fi.upm.es/lpnet/distrib_imp

erial/distrib_imperial.html• Mozart-Oz Documentation• http://www.mozart-oz.org/documentation

127

LP & WWW workshops

• http://www.clip.dia.fi.upm.es/lpnet/iclp97.html

• http://www.informatik.uni-bonn.de/~jicslp96

• http://www.cs.vu.nl/~eliens/WWW6

• http://www.mpi-sb.mpg.de/conferences/CP97

• http://www-lp.doc.ic.ac.uk/lp-internet.html

128

Conclusion

Internet Programming and LP:

• integrated with high level networking, agent programming, external components, various client-server protocols, mobile code

• essential use of multi-threading

• from CGI scripts and HTML to Java and new Web languages VRML, XML etc.

129

Acknowledgements

• Partly based on joint work with Veronica Dahl, Koen DeBosschere, Bart Demoen, Stephen Rochefort, Satyam Tyagi, Anima Gupta, Devender Gollapalli

• Cross-influences –various LP/CLP groups, Madrid, Mozart-Oz, commercial Prologs

• Peter Wilson – port of BinWAM to Java• Java, VRML w3.org – free libraries and tools

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