early in history of artificial intelligence, assumed best way agent choose next compute optimal plan, , execute plan. led physical symbol system hypothesis, physical agent can manipulate symbols necessary , sufficient intelligence. many software agents still use approach action selection. requires describing sensor readings, world, of ones actions , of 1 s goals in form of predicate logic. critics of approach complain slow real-time planning , that, despite proofs, still unlikely produce optimal plans because reducing descriptions of reality logic process prone errors.
satisficing decision-making strategy attempts meet criteria adequacy, rather identify optimal solution. satisficing strategy may often, in fact, (near) optimal if costs of decision-making process itself, such cost of obtaining complete information, considered in outcome calculus.
goal driven architectures – in these symbolic architectures, agent s behaviour typically described set of goals. each goal can achieved process or activity, described prescripted plan. agent must decide process carry on accomplish given goal. plan can expand subgoals, makes process recursive. technically, more or less, plans exploits condition-rules. these architectures reactive or hybrid. classical examples of goal driven architectures implementable refinements of belief-desire-intention architecture jam or ive.
excalibur research project led alexander nareyek featuring any-time planning agents computer games. architecture based on structural constraint satisfaction, advanced artificial intelligence technique.
Comments
Post a Comment