Plan-belief Revision in Jason

Abstract

Abstract:When information is shared between agents of unknown reliability, it is possible that their belief bases become inconsistent. In such cases, the belief base must be revised to restore consistency, so that the agent is able to reason. In some cases the inconsistent information may be due to use of incorrect plans. We extend work by Alechina et al. to revise belief bases in which plans can be dynamically added and removed. We present an implementation of the algorithm in the AgentSpeak implementation Jason.

Normative Monitoring Using Bayesian Networks: Defining a Threshold for Conflict Detection

“…This conflict measure, introduced by Jensen et al [2], was used by Nielsen and Jensen [7] to detect anomalies in production plants based upon sensor readings. In case of normal behaviour, again captured by a BN, the sensor readings should be positively correlated, regardless of whether their combination is rare.…”

Graded Belief Revision for Jason: A Rule-Based Approach

“…A Rule-based agent [11] has a belief base consisting of rules (Horn clauses) and facts (ground literals). The facts can originate from different sources and might change over time as a result of the inference process itself or of the addition and deletion of other facts from the agent's belief base.…”

“…As in [10], [11] for example, we assume that the agent's beliefs are represented in predicate logic, in the form of literals and Horn clause rules. We fix a set of predicate symbols P , a set of variables X, and a set of constants D. A literal α is a predicate symbol of n arguments followed by n variables or constants and possibly preceded by a negation symbol ¬.…”

“…Jensen et al proposed in [11] a non-graded plan-based approach showing practical uses of Nguyen et al's algorithm [12] and extending Alechina et al's [10] to allow for the revision of plans as well, not just beliefs. Besides the fact that they do not take into account degrees of belief, we are not convinced by their proposed non-graded approach.…”