Belief Update in the pGOLOG Framework

High-level controllers that operate robots in dynamic, uncertain domains are concerned with at least two reasoning tasks dealing with the effects of noisy sensors and effectors: They have a) to project the effects of a candidate plan and b) to update their beliefs during on-line execution of a plan. In this paper, we show how the pGOLOG framework, which in its original form only accounted for the projection of high-level plans, can be extended to reason about the way the robot's beliefs evolve during the on-line execution of a plan. pGOLOG, an extension of the high-level programming language GOLOG, allows the specification of probabilistic beliefs about the state of the world and the representation of sensors and effectors which have uncertain, probabilistic outcomes. As an application of belief update, we introduce belief-based programs, GOLOG-style programs whose tests appeal to the agent's beliefs at execution time.

[1]  Daniel S. Weld,et al.  Probabilistic Planning with Information Gathering and Contingent Execution , 1994, AIPS.

[2]  Hector J. Levesque,et al.  Foundations for the Situation Calculus , 1998, Electron. Trans. Artif. Intell..

[3]  Gerhard Lakemeyer,et al.  On-Line Execution of cc-Golog Plans , 2001, IJCAI.

[4]  David Poole,et al.  Decision Theory, the Situation Calculus and Conditional Plans , 1998, Electron. Trans. Artif. Intell..

[5]  Hector J. Levesque,et al.  Reasoning about Noisy Sensors and Effectors in the Situation Calculus , 1995, Artif. Intell..

[6]  Nicholas Kushmerick,et al.  An Algorithm for Probabilistic Planning , 1995, Artif. Intell..

[7]  Wolfram Burgard,et al.  Experiences with an Interactive Museum Tour-Guide Robot , 1999, Artif. Intell..

[8]  Gerhard Lakemeyer,et al.  cc-Golog: Towards More Realistic Logic-Based Robot Controllers , 2000, AAAI/IAAI.

[9]  Craig Boutilier,et al.  Decision-Theoretic, High-Level Agent Programming in the Situation Calculus , 2000, AAAI/IAAI.

[10]  Gerhard Lakemeyer,et al.  Turning High-Level Plans into Robot Programs in Uncertain Domains , 2000, ECAI.

[11]  J. McCarthy Situations, Actions, and Causal Laws , 1963 .

[12]  Ray Reiter,et al.  On knowledge-based programming with sensing in the situation calculus , 2001, ACM Trans. Comput. Log..

[13]  Hector J. Levesque,et al.  What Is Planning in the Presence of Sensing? , 1996, AAAI/IAAI, Vol. 2.

[14]  Hector J. Levesque,et al.  ConGolog, a concurrent programming language based on the situation calculus , 2000, Artif. Intell..

[15]  Hector J. Levesque,et al.  An Incremental Interpreter for High-Level Programs with Sensing , 1999 .

[16]  Leslie Pack Kaelbling,et al.  Planning and Acting in Partially Observable Stochastic Domains , 1998, Artif. Intell..