Dependency-Directed Reconsideration Belief Base Optimization for Truth Maintenance Systems

AAAI Conferences

We define reconsideration, a non-prioritized belief change operation on a finite set of base beliefs. Reconsideration is a hindsight belief change repair that eliminates negative effects caused by the order of previously executed belief change operations. Beliefs that had previously been removed are returned to the base if there no longer are valid reasons for their removal. This might result in less preferred beliefs being removed, and additional beliefs being returned. The end product is an optimization of the belief base, converting the results of a series of revisions to the very base that would have resulted from a batch revision performed after all base beliefs were entered/added. Reconsideration can be done by examining the entire set of all base beliefs (both currently believed and retracted) -- or, if the believed base is consistent, by examining all retracted beliefs for possible return. This, however, is computationally expensive. We present a more efficient, TMSfriendly algorithm, dependency-directed reconsideration (DDR), which can produce the same results by examining only a dynamically determined subset of base beliefs that are actually affected by changes made since the last base optimization process. DDR is an efficient, anytime, belief base optimizing algorithm that eliminates operation order effects.


Belief Revision in a Deductively Open Belief Space

AAAI Conferences

I am researching the traditional belief revision integrity constraints and postulates, which are designed for deductively closed belief spaces, and revising them so that they are applicable to implemented knowledge representation and reasoning systems with deductively open belief spaces (DOBS). A knowledge representation and reasoning system must be able to deal with contradictions and revise beliefs. This is especially important to data fusion, where information is combined from multiple sources, which might contradict each other. Most theoretical postulates for belief revision and belief contraction assume a deductively closed belief space (DCBS), where all beliefs derivable from a belief space are in that belief space. This is hard (or impossible) to produce in an implemented belief revision system, which has real-world limitations on computation time and database size.


Metacognition in SNePS

AI Magazine

The SNePS knowledge representation, reasoning, and acting system has several features that facilitate metacognition in SNePSbased agents. The most prominent is the fact that propositions are represented in SNePS as terms rather than as sentences, so that propositions can occur as arguments of propositions and other expressions without leaving first-order logic. The SNePS acting subsystem is integrated with the SNePS reasoning subsystem in such a way that: there are acts that affect what an agent believes; there are acts that specify knowledge-contingent acts and lack-ofknowledge acts; there are policies that serve as "daemons," triggering acts when certain propositions are believed or wondered about. The GLAIR agent architecture supports metacognition by specifying a location for the source of self-awareness and of a sense of situatedness in the world. Several SNePSbased agents have taken advantage of these facilities to engage in self-awareness and metacognition.


Metacognition in SNePS

AI Magazine

The SNePS knowledge representation, reasoning, and acting system has several features that facilitate metacognition in SNePS-based agents. The most prominent is the fact that propositions are represented in SNePS as terms rather than as sentences, so that propositions can occur as argu- ments of propositions and other expressions without leaving first-order logic. The SNePS acting subsystem is integrated with the SNePS reasoning subsystem in such a way that: there are acts that affect what an agent believes; there are acts that specify knowledge-contingent acts and lack-of-knowledge acts; there are policies that serve as "daemons," triggering acts when certain propositions are believed or wondered about. The GLAIR agent architecture supports metacognition by specifying a location for the source of self-awareness and of a sense of situatedness in the world. Several SNePS-based agents have taken advantage of these facilities to engage in self-awareness and metacognition.


Minimal Change in AGM Revision for Non-Classical Logics

AAAI Conferences

In this paper, we address the problem of applying AGM-style belief revision  to non-classical logics. We discuss the idea of minimal change in revision and show that for non-classical logics, some sort of minimality postulate has to be explicitly introduced. We also present two constructions for revision which satisfy the AGM postulates and prove the representation theorems including minimality postulates.