Ch. 2 – Intelligent Agents Supplemental slides for CSE 327 Prof. Jeff Heflin

Agent Review Agent percepts sensors Environment ? actions actuators ideal rational agent: an agent that always takes the action expected to maximize its performance measure, given the set of percepts (percept sequence) it has seen so far

Table Driven Agent function TABLE-DRIVEN-AGENT(percept) returns an action static: percepts, a sequence, initially empty table, a table of actions, indexed by percept sequences append percept to the end of percepts action  LOOKUP(percepts, table) return action From Figure 2.7, p. 45

Table Driven Agent function name input output type function TABLE-DRIVEN-AGENT(percept) returns an action static: percepts, a sequence, initially empty table, a table of actions, indexed by percept sequences append percept to the end of percepts action  LOOKUP(percepts, table) return action From Figure 2.7, p. 45 assignment operation function call output value static variables: maintain values between function calls, like instance variables in OO, but can only be referenced within the function

Rock, Scissors, Paper Table Driven Agent Percept Sequence Action <Start> Rock <Start, Win(Rock,Scissors)> <Start, Lose(Rock,Paper)> Scissors <Start, Tie(Rock,Rock)> Paper <Start, Win(Rock,Scissors), Win (Rock,Scissors)> <Start, Win(Rock,Scissors), Lose(Rock,Paper)> <Start, Win(Rock,Scissors), Tie(Rock,Rock)> <Start, Lose(Rock,Paper), Win(Scissors,Paper)> <Start, Lose(Rock,Paper), Lose(Scissors,Rock)> <Start, Lose(Rock,Paper), Tie(Scissors,Scissors)> …. …