654 research outputs found
Semantics and Conversations for an Agent Communication Language
We address the issues of semantics and conversations for agent communication
languages and the Knowledge Query Manipulation Language (KQML) in particular.
Based on ideas from speech act theory, we present a semantic description for
KQML that associates ``cognitive'' states of the agent with the use of the
language's primitives (performatives). We have used this approach to describe
the semantics for the whole set of reserved KQML performatives. Building on the
semantics, we devise the conversation policies, i.e., a formal description of
how KQML performatives may be combined into KQML exchanges (conversations),
using a Definite Clause Grammar. Our research offers methods for a speech act
theory-based semantic description of a language of communication acts and for
the specification of the protocols associated with these acts. Languages of
communication acts address the issue of communication among software
applications at a level of abstraction that is useful to the emerging software
agents paradigm.Comment: Also in in "Readings in Agents", Michael Huhns and Munindar Singh
(eds), Morgan Kaufmann Publishers, In
PROLOG META-INTERPRETERS FOR RULE-BASED INFERENCE UNDER UNCERTAINTY
Uncertain facts and inexact rules can be represented and
processed in standard Prolog through meta-interpretation. This
requires the specification of appropriate parsers and belief
calculi. We present a meta-interpreter that takes a rule-based
belief calculus as an external variable. The certainty-factors
calculus and a heuristic Bayesian belief-update model are then
implemented as stand-alone Prolog predicates. These, in turn,
are bound to the meta-interpreter environment through second-order
programming. The resulting system is a powerful
experimental tool which enables inquiry into the impact of
various designs of belief calculi on the external validity of
expert systems. The paper also demonstrates the (well-known)
role of Prolog meta-interpreters in building expert system
shells.Information Systems Working Papers Serie
META-INTERPRETERS FOR RULE-BASED REASONING UNDER UNCERTAINTY
One of the key challenges in designing expert systems is a credible representation
of uncertainty and partial belief. During the past decade, a number of
rule-based belief languages were proposed and implemented in applied systems.
Due to their quasi-probabilistic nature, the external validity of these
languages is an open question. This paper discusses the theory of belief revision
in expert systems through a canonical belief calculus model which is
invariant across different languages. A meta-interpreter for non-categorical
reasoning is then presented. The purposes of this logic model is twofold:
first, it provides a clear and concise conceptualization of belief representation
and propagation in rule-based systems. Second, it serves as a working
shell which can be instantiated with different belief calculi. This enables
experiments to investigate the net impact of alternative belief languages on
the external validity of a fixed expert system.Information Systems Working Papers Serie
Abductive Reasoning in Multiple Fault Diagnosis
Abductive reasoning involves generating an explanation for a given set of observations about the world. Abduction provides a good reasoning framework for many AI problems, including diagnosis, plan recognition and learning. This paper focuses on the use of abductive reasoning in diagnostic systems in which there may be more than one underlying cause for the observed symptoms. In exploring this topic, we will review and compare several different approaches, including Binary Choice Bayesian, Sequential Bayesian, Causal Model Based Abduction, Parsimonious Set Covering, and the use of First Order Logic. Throughout the paper we will use as an example a simple diagnostic problem involving automotive troubleshooting
A Hierarchical Database Model for a Logic Programming Language
This paper presents an extended Clausal Database Model for a logic programming language. Instead of being restricted to one global database, as is the case with Prolog, we allow segmentation of the database into database units which are linked together into a semi-lattice. Each database unit defines a database view which includes clauses which have been asserted into that unit as well as clauses inherited from its ancestors higher in the lattice structure. This model supports arbitrary retraction. Retracting a clause in a database unit effectively blocks its inheritance for that unit and all of its descendants. Motivations for using this model are given. We also discuss the implementation of a Prolog meta-interpreter that uses this model. (hereafter referred to as (Phd) or Prolog Hierarchical Database) This meta-interpreter is in the spirit of Prolog and therefore has a version of assert, retract and cut
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