COMP 102 Lecture Notes - Lecture 20: Memory Stick, Linear Combination, Microsoft Onenote
22 Mar 2016
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Document Summary
Example ai system: ibm deep blue v. garry kasparov. Percepion advanced features of the board. Reasoning: search and evaluaion of possible board posiions. Game playing: oldest, most well studied ai domain, public preference, viewed as an indicator of int. Oten stochasicity and imperfect informaion is there. Clear, clean env descripion: easy performance indicator. Games : ai = grand prix : car design. Cpu: pro fast, good at repeiion, bad value judgments, need to covert the order in an exact order in programming language. Ai games characterisics: usually computer games are really good at complicated posiions analysis w/ many opions, bad at outlying scenarios. Typical strategy v. cpu try to tric it i/t going for something that isn"t good. State space s: all possible conig of the domain. Iniial state s0 s: the start state. Goal states g s: the set of end states. Acions a: the set of available moves. Path: a sequence of states and operators.
