Preference-based belief revision for rule-based agents

Abstract

Abstract. Agents which perform inferences on the basis of unreliable information need an ability to revise their beliefs if they discover an inconsistency. Such a belief revision algorithm ideally should be rational, should respect any preference ordering over the agent's beliefs (removing less preferred beliefs where possible) and should be fast. However, while standard approaches to rational belief revision for classical reasoners allow preferences to be taken into account, they typically have quite high complexity. In this paper, we consider belief revision for agents which reason in a simpler logic than full first-order logic, namely rule-based reasoners. We show that it is possible to define a contraction operation for rule-based reasoners, which we call McAllester contraction, which satisfies all the basic Alchourrón, Gärdenfors and Makinson (AGM) postulates for contraction (apart from the recovery postulate) and at the same time can be computed in polynomial time. We prove a representation theorem for McAllester contraction with respect to the basic AGM postulates (minus recovery), and two additional postulates. We then show that our contraction operation removes a set of beliefs which is least preferred, with respect to a natural interpretation of preference. Finally, we show how McAllester contraction can be used to define a revision operation which is also polynomial time, and prove a representation theorem for the revision operation.

Plan-belief Revision in Jason

“…Other recent work on approaches to inconsistency handling in Jason and related systems should also be considered (Alechina et al, 2008;Klapiscak and Bordini, 2009;Villadsen, 2005;Fuzitaki et al, 2010;Mascardi et al, 2011;Jensen and Villadsen, 2012;Spurkeland et al, 2013).…”

BDI Logics for BDI Architectures: Old Problems, New Perspectives

“…For example, the language of AgentSpeak does not enable reasoning about the consequences of an action. The main exception is Meyer et al work on the KARO framework [1,4,29]. However, it seems to be fair to say that this logic and its mathematical properties are not well understood yet.…”

“…His central idea is that beliefs and intentions-to-do are organized in two temporal databases. A belief database B is a set of pairs made up of time points t in the set of non-negative integers N 0 and literals p. 4 They are written p t and read ''p is true at t''. Similarly, an intention database I is a set of pairs made up of time points t and (basic) actions a.…”

“…While such revisions naturally also modify the agent's goals, the belief revision literature basically never studied intention revision. In contrast, the BDI literature contains some papers accounting for this dynamic aspect [2,4,31,36,60].…”

A defeasible logic for modelling policy-based intentions and motivational attitudes

“…When dealing with such personal policies we have to take into account two cases. Policy-based intentions could be either (1) periodic or (2) 3 If I begin with the intended end of running today, but balk at some necessary means to so acting I will be rationally obliged to give up my intended end. This contrasts with a case in which one does not apply a policy to a particular case due to that policy's defeasibility; for in this latter case the fact that one does not settle on a specification of the policy in the particular case does not force one to give up the policy.…”