Abductive reasoning

About: Abductive reasoning is a research topic. Over the lifetime, 1917 publications have been published within this topic receiving 44645 citations. The topic is also known as: abduction & abductive inference.

A probabilistic approach to marker propagation

Abstract: Potentially, the advantages of marker-passing over local connectionist techniques for associative inference are (1) the ability to differentiate variable bindings, and (2) reduction in the search space and/or number of processing elements. However, the latter advantage has mostly been realized at the expense of accuracy and predictability. In this paper we consider a class of associative inference to which marker passing is often applied, variously called abductive inference, schema selection, or pattern completion. Analysis of marker semantics in a standard semantic net representation leads to a proposal for more strictly regulated marker propagation. An implementation strategy employing an augmented relaxation network is outlined.

FIRE: Infrastructure for Experience-based Systems with Common Sense

Abstract: We believe that the flexibility and robustness of common sense reasoning comes from analogical reasoning, learning, and generalization operating over massive amounts of experience. Million-fact knowledge bases are a good starting point, but are likely to be orders of magnitude smaller, in terms of ground facts, than will be needed to achieve human-like common sense reasoning. This paper describes the FIRE reasoning engine which we have built to experiment with this approach. We discuss its knowledge base organization, including coarse-coding via mentions and a persistent TMS to achieve efficient retrieval while respecting the logical environment formed by contexts and their relationships in the KB. We describe its stratified reasoning organization, which supports both reflexive reasoning (Ask, Query) and deliberative reasoning (Solve, HTN planner). Analogical reasoning, learning, and generalization are supported as part of reflexive reasoning. To show the utility of these ideas, we describe how they are used in the Companion cognitive architecture, which has been used in a variety of reasoning and learning experiments.