TY - GEN
T1 - Exploring heuristic action selection in agent programming
AU - Hindriks, Koen V.
AU - Jonker, Catholijn M.
AU - Pasman, Wouter
PY - 2009/9/28
Y1 - 2009/9/28
N2 - Rational agents programmed in agent programming lan- guages derive their choice of action from their beliefs and goals. One of the main benefits of such programming languages is that they facilitate a high-level and conceptually elegant specification of agent behaviour. Qualitative concepts alone, however, are not sufficient to specify that this behaviour is also nearly optimal, a quality typically also associated with rational agents. Optimality in this context refers to the costs and rewards associated with action execution. It thus would be useful to extend agent programming languages with primitives that allow the specification of near-optimal behaviour. The idea is that quantitative heuristics added to an agent program prune some of the options generated by the qualitative action selection mechanism. In this paper, we explore the expressivity needed to specify such behaviour in the Blocks World domain. The programming constructs that we introduce allow for a high-level specification of such heuristics due to the fact that these can be defined by (re)using the qualitative notions of the basic agent programming language again. We illustrate the use of these constructs by extending a Goal Blocks World agent with various strategies to optimize its behaviour.
AB - Rational agents programmed in agent programming lan- guages derive their choice of action from their beliefs and goals. One of the main benefits of such programming languages is that they facilitate a high-level and conceptually elegant specification of agent behaviour. Qualitative concepts alone, however, are not sufficient to specify that this behaviour is also nearly optimal, a quality typically also associated with rational agents. Optimality in this context refers to the costs and rewards associated with action execution. It thus would be useful to extend agent programming languages with primitives that allow the specification of near-optimal behaviour. The idea is that quantitative heuristics added to an agent program prune some of the options generated by the qualitative action selection mechanism. In this paper, we explore the expressivity needed to specify such behaviour in the Blocks World domain. The programming constructs that we introduce allow for a high-level specification of such heuristics due to the fact that these can be defined by (re)using the qualitative notions of the basic agent programming language again. We illustrate the use of these constructs by extending a Goal Blocks World agent with various strategies to optimize its behaviour.
UR - https://www.scopus.com/pages/publications/70349322596
UR - https://www.scopus.com/pages/publications/70349322596#tab=citedBy
U2 - 10.1007/978-3-642-03278-3_2
DO - 10.1007/978-3-642-03278-3_2
M3 - Conference contribution
AN - SCOPUS:70349322596
SN - 364203277X
SN - 9783642032776
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 24
EP - 39
BT - Programming Multi-Agent Systems - 6th International Workshop, ProMAS 2008, Revised Invited and Selected Papers
T2 - 6th International Workshop on Programming Multi-Agent Systems, ProMAS 2008
Y2 - 13 May 2008 through 13 May 2008
ER -