TY - GEN
T1 - Progression with probabilities in the Situation Calculus
T2 - The 23rd International Conference on Autonomous Agents and Multiagent Systems<br/>
AU - Liu, Daxin
AU - Belle, Vaishak
N1 - Conference code: 23
PY - 2024/5/6
Y1 - 2024/5/6
N2 - Progression in the Situation Calculus is perhaps one of the most extensively studied cases of updating logical theories over a sequence of actions. While it generally requires second-order logic, several useful first-order and tractable cases have been identified. Recently, there has been an interest in studying the progression of probabilistic knowledge bases expressed using degrees of belief on first-order formulas. However, although a few results exist, they do not provide much clarity about how this progression can be computed or represented in a feasible manner. In this paper, we address this problem for the first time. We first examine the progression of a probabilistic knowledge base (PKB) in a world-level representation; in particular, we show that such a representation is closed under progression for any local-effect actions with quantifier-free contexts. We also propose a more succinct representation of the probabilistic knowledge base, i.e. factored-representation PKB. For this type of PKB, we study the conditions for progression to remain succinct.
AB - Progression in the Situation Calculus is perhaps one of the most extensively studied cases of updating logical theories over a sequence of actions. While it generally requires second-order logic, several useful first-order and tractable cases have been identified. Recently, there has been an interest in studying the progression of probabilistic knowledge bases expressed using degrees of belief on first-order formulas. However, although a few results exist, they do not provide much clarity about how this progression can be computed or represented in a feasible manner. In this paper, we address this problem for the first time. We first examine the progression of a probabilistic knowledge base (PKB) in a world-level representation; in particular, we show that such a representation is closed under progression for any local-effect actions with quantifier-free contexts. We also propose a more succinct representation of the probabilistic knowledge base, i.e. factored-representation PKB. For this type of PKB, we study the conditions for progression to remain succinct.
KW - knowledge representation
KW - probabilistic progression
KW - reasoning about action
U2 - 10.5555/3635637.3662978
DO - 10.5555/3635637.3662978
M3 - Conference contribution
SN - 9798400704864
SP - 1210
EP - 1218
BT - Proceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems
PB - ACM
Y2 - 6 May 2024 through 10 May 2024
ER -