UCT CS Research Document Archive

A Stochastic Belief Management Architecture for Agent Control

Rens, Gavin, Thomas Meyer and Deshendran Moodley (2017) A Stochastic Belief Management Architecture for Agent Control. In Thorisson, Kristin, Pei Wang, Kamilla Johannsdotter, Joshua Bach and Jordi Bieger, Eds. Proceedings IJCAI-17 Workshop on ARCHITECTURES FOR GENERALITY & AUTONOMY, Melbourne, Australia.

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Abstract

We propose an architecture for agent control, where the agent stores its beliefs and environ- ment models as logical sentences. Given succes- sive observations, the agent’s current state (of be- liefs) is maintained by a combination of proba- bility, POMDP and belief change theory. Two ex- isting logics are employed for knowledge repre- sentation and reasoning: the stochastic decision logic of Rens et al. (2015) and p-logic of Zhuang et al. (2017) (a restricted version of a logic de- signed by Fagin et al. (1990)). The proposed ar- chitecture assumes two streams of observations: active, which correspond to agent intentions and passive, which is received without the agent’s di- rect involvement. Stochastic uncertainty, and ig- norance due to lack of information are both dealt with in the architecture. Planning, and learning of environment models are assumed present but are not covered in this proposal.

EPrint Type:Conference Paper
Subjects:I Computing Methodologies: I.2 ARTIFICIAL INTELLIGENCE
ID Code:1201
Deposited By:Meyer, Thomas
Deposited On:23 November 2017
Alternative Locations:http://cadia.ru.is/workshops/aga2017/proceedings/AGA_2017_Rens_et_al.pdf