A Stochastic Belief Management Architecture for Agent Control

Rens, Gavin and Meyer, Thomas and Moodley, Deshendran (2017) A Stochastic Belief Management Architecture for Agent Control, Proceedings of IJCAI-17 Workshop on ARCHITECTURES FOR GENERALITY & AUTONOMY, 19 August, Melbourne, Australia.

[img] PDF

Download (345kB)


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.

Item Type: Conference paper
Subjects: Computing methodologies > Artificial intelligence
Alternate Locations: http://cadia.ru.is/workshops/aga2017/proceedings/AGA_2017_Rens_et_al.pdf
Date Deposited: 23 Nov 2017
Last Modified: 10 Oct 2019 15:31
URI: http://pubs.cs.uct.ac.za/id/eprint/1201

Actions (login required)

View Item View Item