Procedural Reasoning System Research Articles

A logic of intention and action for regular BDI agents based on bisimulation of agent programs

We address the problem of providing a computationally grounded semantics for belief, desire, intention (BDI) agents that explicitly relates intention to action, using as a basis for this connection a notion of bisimulation for agent programs. We first define regular BDI agents, a class of BDI agents inspired by the procedural reasoning system architecture, under the restriction that agent programs are representable as regular expressions. The operational semantics of regular agent programs is formalized using agent program execution graphs, an extension of the process graphs used to formalize regular processes. An agent's executed program represents an attempt to perform an intended plan and can include branches for both successful execution and the failure of action attempts; intended execution paths are defined in terms of successful executions, and intentions in terms of future successfully executed agent programs. We present Agent Dynamic Logic ($$\mathsf {ADL}$$ADL), a logic of intention and action that faithfully represents the operational semantics of regular BDI agents. $$\mathsf {ADL}$$ADL is a logic in the spirit of BDI logic but also includes the dynamic logic of actions and a reduction of the logic of intention to the logics of action and time. A main contribution of the paper is a completeness result for a subclass of finite $$\mathsf {ADL}$$ADL theories with explicit representations of agent plans.

A Review of Cognitive Decision-making within Future Mission Systems

This paper provides an outline of historical attempts to achieve human-like decision-making within machines. It concludes with a proposed conceptual approach of how researchers might pursue cognitive mission systems designs in the future. A number of potential success stories need to be explored in order to revise existing techniques and identify which techniques could be componentised for use in this future design. Existing cognitive systems have evolved over time, using; LISt Pro- cessing (LISP), PROLOG and Object Oriented Programming (OOP) languages. These were used to represent information using lists, scripts, frames, schemas, production rules, procedural, semantic and declarative processes. As Computational Intelligence (CI) techniques evolved, a number of frameworks emerged; such as Recognition-Primed Decision (RPD), Pro- cedural Reasoning System (PRS), Collaborative Agent for Simulating Teamwork (CAST), Adaptive Character of Thought– Rational (ACT-R), distributed Multi-Agent Reasoning System (dMars), State, Operator And Result (SOAR) and Java Agent Compiler and Kernel (JACK). Many of these failed to gain traction because the problem-space has become more complex and existing heuristic code quickly becomes unwieldy with no guaranteed solution. Although currently heuristic systems relieve humans of routine activities, they are not able to independently reproduce intuition, insight or cognitive learning. Researchers have repetitively attempted to enhance the level of decision-making capabilities, but few have achieved success without aug- mented human support. Emerging frameworks continue to re-use a number of recurring themes to solve constrained problems, although most techniques cannot transform information into knowledge or wisdom. This paper highlights a number of the more successful concepts that could be used to progressively derive components to form a working cognitive decision-making model within a future mission system.

The dMARS Architecture: A Specification of the Distributed Multi-Agent Reasoning System

The Procedural Reasoning System (PRS) is the best established agent architecture currently available. It has been deployed in many major industrial applications, ranging from fault diagnosis on the space shuttle to air traffic management and business process control. The theory of PRS-like systems has also been widely studied: within the intelligent agents research community, the belief-desire-intention (BDI) model of practical reasoning that underpins PRS is arguably the dominant force in the theoretical foundations of rational agency. Despite the interest in PRS and BDI agents, no complete attempt has yet been made to precisely specify the behaviour of real PRS systems. This has led to the development of a range of systems that claim to conform to the PRS model, but which differ from it in many important respects. Our aim in this paper is to rectify this omission. We provide an abstract formal model of an idealised dMARS system (the most recent implementation of the PRS architecture), which precisely defines the key data structures present within the architecture and the operations that manipulate these structures. We focus in particular on dMARS plans, since these are the key tool for programming dMARS agents. The specification we present will enable other implementations of PRS to be easily developed, and will serve as a benchmark against which future architectural enhancements can be evaluated.

An architecture for real-time reasoning and system control

The Procedural Reasoning System, a generic reasoning system based on the rational-agent architecture, is described. The system has been applied to several real-time applications, including mobile robot control, system control for a surveillance aircraft, and air traffic management. Two applications that are relevant to process industries handling malfunctions for the reaction control system of NASA's Space Shuttle and diagnosing and controlling failures and overloads in a telecommunications network are discussed. Specifically, the representation and management of malfunction-handling procedures and tasks. >