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The UNC major with the highest average salary is Geology ... What do these actions have in common? smoking 1.4 cigarettes drinking 0.5 liter of wine spending 1 ...
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Advanced Artificial Intelligence Lecture 3: Adversarial Search(Game) *
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Adversarial Search This deck courtesy of Dan Klein at UC Berkeley * * * * * * * * * * * * * * * * * * * Example: Cryptarithmetic Variables (circles): Domains ...
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Dan Klein UC Berkeley. Many s over the course adapted from either ... In solitaire, shuffle is unknown. In minesweeper, don't know where the mines are ...
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Online Sampling for Markov Decision Processes Bob Givan Joint work w/ E. K. P. Chong, H. Chang, G. Wu Electrical and Computer Engineering Purdue University
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RECAP CSE 348 AI Game Programming H ctor Mu oz-Avila
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Adversarial Search Game Playing Chapter 6 Outline Games Perfect Play Minimax decisions - pruning Resource Limits and Approximate Evaluation Games of chance Games ...
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Markov Decision Process (MDP) Ingredients: System state x in state space X Control action a in A(x) Reward R(x,a) ... Two-pronged solution approach: ...
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Course Overview and summary We have discussed - What AI and intelligent agents are - How to develop AI systems - How to solve problems using search
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Abstraction: To describe a game we must capture every relevant aspect of the game. ... E.g, w's could be the values of pieces (1 for prawn, 3 for bishop etc. ...
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Metric-Temporal Planning: Issues and Representation. Search ... (belief) state action tables. Deterministic Success: Must reach goal-state with probability 1 ...
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The approaches we have discussed do not guarantee optimality or even near ... Use domain knowledge to handcraft a more intelligent default policy than random ...
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(Waltz, 1975; Mackworth, 1977) Constraint Propagation. 15. Edge Labeling as a CSP ... (Waltz, 1975; Mackworth, 1977) Constraint Propagation. 22. General CP for ...
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loop for b in succ(board) b-val = minimax(b,depth-1,max) cur-min = min(b-val,cur-min) ... if cur-max = b finish loop. return cur-max. else type = min. cur-min = inf ...
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What if you see this as a game? RTA* (RTDP with deterministic actions and leaves evaluated by f(.)) Game Playing (Adversarial Search) ...
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Title: CS 561a: Introduction to Artificial Intelligence Author: Paolo Pirjanian Last modified by: bhecker Created Date: 8/30/2000 3:22:35 AM Document presentation format
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Title: Intelligenza Artificiale Author: Marco Ernandes Last modified by: Marco Gori Created Date: 2/3/2004 8:29:02 AM Document presentation format
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Example features for chess are piece count, piece placement, squares controlled, etc. ... Chess: Deep Blue defeated human world champion Garry Kasparov in a ...
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USAir America West Route Map. Chp. 3, 4: Searches. Blind Searches. Breadth-first search ... What makes a good heuristic (admissable, consistent,...) How to ...
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Fun. Interesting, hard problems which require minimal 'initial structure' ... http://www.cnn.com/2003/TECH/fun.games/11/19/kasparov.chess.ap ...
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Desires. Sensory Input. Proximity to items of interest (Jon ... Location of players. Map is generated step-wise by adding clumps. Transport units in RTS games: ...
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Homework 4 will be due before the last class ... looks all directions every 3 millimeters of driving; also Sphexishness) [XII/Puccini project] ...
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Othello: human champions refuse to compete against computers, who are too good. Go: human champions refuse to compete against computers, who are too bad.
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How to play games as an application/extension of search ... Is search applicable to game playing? ... best play. Algorithm: Generate game tree completely ...
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How to play games as an application/extension of search ... Is search applicable to game playing? ... best play. Algorithm: Generate game tree completely ...
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Some material adopted from notes by Charles R. Dyer, University of ... Clear ... Deep Junior (Feb 2003): tie! Kasparov vs. X3D Fritz (November 2003): tie! ...
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Chess: b = 35, m=100 nodes = 100 35. if each node takes about 1 ... EVAL: evaluation function to replace utility function (e.g., number of chess pieces taken) ...
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Sketch of Chess History. First discussed by Shannon, Sci. American, 1950 ... Sketch of Chess History. Chess 4.x reaches 2000 (expert level), 1979. Belle 2200, 1983 ...
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7.1.3 Epistemic Types. Recall: Players really only uncertain about the game's ... Use the epistemic type definition of Bayesian game because it's the most ...
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Construct a sample determinization by 'simulating' each stochastic action to pick the outcome. ... Upper bound (ub): for policy computation. gap(s) = ub(s) lb ...
Infinite horizon discounted: discounting keeps total bounded ... Discounted Infinite Horizon MDPs. Total reward problematic (usually) ...
