AI Wolf Contest -Development of Game AI using Collective Intelligence-
An AI Game Project
description
Transcript of An AI Game Project
An AI Game Project
Background• Fivel is a unique combiation of a NxM game and a sliding puzzle.
• The goals in making this projects were:
• Create an original game experience. • Create a challenging AI player using optimized calculations.• Achieve an attractive visual look (cute and funny woodland
creatures).• Accessibility – Easy-to-use UI.• The Future? The ability to export the game to the web
upon completion.
The GameEach turn, a player puts a piece in an
empty slot, and slides a tile to an empty
place.
The GameEach turn, a player puts a piece in an
empty slot, and slides a tile to an empty
place.
The GameEach turn, a player puts a piece in an
empty slot, and slides a tile to an empty
place.
The GameEach turn, a player puts a piece in an
empty slot, and slides a tile to an empty
place.
The GameEach turn, a player puts a piece in an
empty slot, and slides a tile to an empty
place.
The GameThe first player to place 5 pieces in a
row, column or diagonal at the end of
his turn, wins.
The GameThe first player to place 5 pieces in a
row, column or diagonal at the end of
his turn, wins.
The GameThe first player to place 5 pieces in a
row, column or diagonal at the end of
his turn, wins.
The GameThe first player to place 5 pieces in a
row, column or diagonal at the end of
his turn, wins.
Development
Flash/AS3 • PROS: • Allows to create great presentations and UI’s easily and
fast.• Accessibility.
• CONS: • AS3 is considerably slow.• Flash has a problems with deep-recursions (15 seconds
limit and rendering halting without the use of chunking).
• Problem: Good presentation VS. Strong and reliable computation.
• Problem: Good presentation VS. Strong and reliable computation.
Java • PROS: • Fast and reliable for deep recursions.• Everybody knows Java!
• CONS: • Harder to achieve the visual look we were looking for.• Graphical programming in JAVA is relatively complicated.
Development
HTMLWrapper
JavaScriptInterface
Flex/AS3 FrontendGUI
Java BackendData Structure, Logic and AI
Architecture
Data Structure• The board is based on
“Fivlets” (“Winning Fives”).
• These are sets of indices that form a winning row, column or diagonal.
• The board statically stores all the 32 Fivlets in the game.
Example for Row Fivlets
Data Structure• Each Fivlet knows the status of
the 5 slots it contains.
• This structure allows to perform various calculations faster than other methods.
• Moves are easy to perform (bounded by number of Fivlets the modified slots are in).
Example for Column and Diagonal Fivlets
• Iterate over all Fivlets [O(1)] in order to check for winning conditions and base the heuristics upon their state.
AI and Heuristics• Automatic players in Fivel use α&β pruning algorithm to
search for an optimal move.
• The depth of the search is determined by the user when choosing difficulty through the GUI. We supply 4 different levels of difficulty:
Beginner – Depth 2 Experienced – Depth 3.Tough – Depth 4 Godlike – Depth 5.
AI and Heuristics• As the search algorithm deepens, Move objects are generated
and performed on the data structure. Each Move objects has an Undo method in order to restore the board.
• These operations are low-cost due to the use of Fivlets.
• Although moves in Fivel consist actually of two different operations (piece placement and then tile sliding), they are considered as a single move in the game logic.
AI and Heuristics• When a terminal board node is reached (either a board at an
end state or when the algorithm reached its designated depth) it is rated according to the following algorithm:
For each Fivlet in BoardFor each Slot in Fivlet
If Slot is Mine then mine += 1Else if Slot is Opponent then opp += 1
If mine == 5 then score = BIG_CONSTElse if opp == 5 then score = -BIG_CONSTElse if mine == 0 and opp > 0 then score -= -opp^NElse if opp == 0 and mine > 0 then score += mine^M
Return score
AI and Heuristics• Basically, the algorithm iterates over all Fivlets and rates each
one. Eventually it sums up all the scores and returns it as the board’s heuristic score.
For each Fivlet in BoardFor each Slot in Fivlet
If Slot is Mine then mine += 1Else if Slot is Opponent then opp += 1
If mine == 5 then score = BIG_CONSTElse if opp == 5 then score = -BIG_CONSTElse if mine == 0 and opp > 0 then score -= -opp^NElse if opp == 0 and mine > 0 then score += mine^M
Return score
AI and Heuristics• The algorithm counts how many pieces the current player and
his opponent placed in each Fivlet. Empty (no piece) or Void (no tile) slots are not counted and treated the same.
For each Fivlet in BoardFor each Slot in Fivlet
If Slot is Mine then mine += 1Else if Slot is Opponent then opp += 1
If mine == 5 then score = BIG_CONSTElse if opp == 5 then score = -BIG_CONSTElse if mine == 0 and opp > 0 then score -= -opp^NElse if opp == 0 and mine > 0 then score += mine^M
Return score
AI and Heuristics• The Fivlet score is now calculated according to various cases: if
The current player has a full Fivlet, the Fivlet is rated with a high score.
For each Fivlet in BoardFor each Slot in Fivlet
If Slot is Mine then mine += 1Else if Slot is Opponent then opp += 1
If mine == 5 then score = BIG_CONSTElse if opp == 5 then score = -BIG_CONSTElse if mine == 0 and opp > 0 then score -= -opp^NElse if opp == 0 and mine > 0 then score += mine^M
Return score
AI and Heuristics• Similarly, if the opponent of the current player has a full Fivlet,
the Fivlet is rated with a negative high score.
For each Fivlet in BoardFor each Slot in Fivlet
If Slot is Mine then mine += 1Else if Slot is Opponent then opp += 1
If mine == 5 then score = BIG_CONSTElse if opp == 5 then score = -BIG_CONSTElse if mine == 0 and opp > 0 then score -= -opp^NElse if opp == 0 and mine > 0 then score += mine^M
Return score
AI and Heuristics• If a player has pieces in a Fivlet without an interference from
his opponent, the Fivlet is exponentially scored based on the number of pieces in that Fivlet.
For each Fivlet in BoardFor each Slot in Fivlet
If Slot is Mine then mine += 1Else if Slot is Opponent then opp += 1
If mine == 5 then score = BIG_CONSTElse if opp == 5 then score = -BIG_CONSTElse if mine == 0 and opp > 0 then score -= -opp^NElse if opp == 0 and mine > 0 then score += mine^M
Return score
AI and Heuristics• Why BIG_CONST and not INFINITY?
If more than one Fivlet is full (which is obviously better than one), the board’s score will still be INFINITY (INF + INF = INF).
For each Fivlet in BoardFor each Slot in Fivlet
If Slot is Mine then mine += 1Else if Slot is Opponent then opp += 1
If mine == 5 then score = BIG_CONSTElse if opp == 5 then score = -BIG_CONSTElse if mine == 0 and opp > 0 then score -= -opp^NElse if opp == 0 and mine > 0 then score += mine^M
Return score
AI and Heuristics• M and N? M is greater than N since playing aggressively
(striving for full Fivlets) has better priority than playing defensively (stopping the opponent from achieving full Fivlets).
For each Fivlet in BoardFor each Slot in Fivlet
If Slot is Mine then mine += 1Else if Slot is Opponent then opp += 1
If mine == 5 then score = BIG_CONSTElse if opp == 5 then score = -BIG_CONSTElse if mine == 0 and opp > 0 then score -= -opp^NElse if opp == 0 and mine > 0 then score += mine^M
Return score
AI Analysis
Average Game Length(Mutual Turns)
Results Number of Games Tested
Match Type
20 Victories 50%Draw 0%
20 Human VS.
Human
20 Human won 40%CPU won 60%
Draw 0%
20 Human VS.
CPU (Beginner)
20 Human won 40%CPU won 60%
Draw 0%
20 Human VS.
CPU (Experienced)
20 Human won 40%CPU won 60%
Draw 0%
20 Human VS.
CPU (Tough)
20 Human won 40%CPU won 60%
Draw 0%
20 Human VS.
CPU (Godlike)
Human
AI Analysis
Average Game Length(Mutual Turns)
Results Number of Games Tested
Match Type
20 Victories %100Draw 0%
20 CPU (Beginner)VS.
CPU (Beginner)
20 Weaker CPU won 40%Stronger CPU won 60%
Draw 0%
20 CPU (Beginner)VS.
CPU (Experienced)
20 Weaker CPU won 40%Stronger CPU won 60%
Draw 0%
20 CPU (Beginner) VS.
CPU (Tough)
20 Weaker CPU won 40%Stronger CPU won 60%
Draw 0%
20 CPU (Beginner)VS.
CPU (Godlike)
Beginner
AI Analysis
Average Game Length(Mutual Turns)
Results Number of Games Tested
Match Type
20 Victories 100%Draw 0%
20 CPU (Experienced)VS.
CPU (Experienced)
20 Weaker CPU won 40%Stronger CPU won 60%
Draw 0%
20 CPU (Experienced) VS.
CPU (Tough)
20 Weaker CPU won 40%Stronger CPU won 60%
Draw 0%
20 CPU (Experienced)VS.
CPU (Godlike)
Experienced
AI Analysis
Average Game Length(Mutual Turns)
Results Number of Games Tested
Match Type
20 Victories 100%Draw 0%
20 CPU (Tough) VS.
CPU (Tough)
20 Weaker CPU won 40%Stronger CPU won 60%
Draw 0%
20 CPU (Tough)VS.
CPU (Godlike)
Tough
AI Analysis
Average Game Length(Mutual Turns)
Results Number of Games Tested
Match Type
20 Victories 100%Draw 0%
20 CPU (Godlike)VS.
CPU (Godlike)
Godlike
Enjoy the Game!
woot?