Knowledge and common knowledge in a distributed environment
Journal of the ACM (JACM)
Artificial intelligence and mathematical theory of computation
Out of control: the new biology of machines, social systems, and the economic world
Out of control: the new biology of machines, social systems, and the economic world
Controlling cooperative problem solving in industrial multi-agent systems using joint intentions
Artificial Intelligence
Hidden order: how adaptation builds complexity
Hidden order: how adaptation builds complexity
Some contributions to the metatheory of the situation calculus
Journal of the ACM (JACM)
First-Order Dynamic Logic
Knowledge, action, and the frame problem
Artificial Intelligence
Experience Using Formal Methods for Specifying a Multi-Agent System
ICECCS '00 Proceedings of the 6th IEEE International Conference on Complex Computer Systems
Multi-agent coordination and control using stigmergy
Computers in Industry
Verification of NASA Emergent Systems
ICECCS '04 Proceedings of the Ninth IEEE International Conference on Engineering Complex Computer Systems Navigating Complexity in the e-Engineering Age
The dawning of the autonomic computing era
IBM Systems Journal
Basic Concepts and Taxonomy of Dependable and Secure Computing
IEEE Transactions on Dependable and Secure Computing
Autonomic Computing for Pervasive ICT — A Whole-System Perspective
BT Technology Journal
Adjustable Deliberation of Self-Managing Systems
ECBS '05 Proceedings of the 12th IEEE International Conference and Workshops on Engineering of Computer-Based Systems
Semantic Information Processing
Semantic Information Processing
From wetware to software: a cybernetic perspective of self-adaptive software
IWSAS'01 Proceedings of the 2nd international conference on Self-adaptive software: applications
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In a complex dynamic system the centralised control and local monitoring of system behaviour is not achievable by scaling up simple feedback adaptation and control models. This paper proposes using a variety of concepts from distributed artificial intelligence (DAI) to logically model an abstract system control using adaptable agent federations to induce self-organisation in a swarm type system. The knowledge acquisition and updates are handled through a modal logic of belief for team dynamics and the system as a whole evolves to learn from local failures that have minimal impact on the global system. Self-governance emerges from innate (given) action thresholds that are adapted dynamically to system demands. In this way it is shown that such a system conforms to the prerequisites that have been specified as necessary for a system to exhibit self-organisation and the intrinsic benefits of agent teamwork are established for a robust, reliable and agile system. The approach is illustrated by looking at team formation in a swarm scenario from a proposed NASA project. The Situation Calculus is used to formalise the dynamic nature of such systems with a dynamic logic implementation to reason about the ensuing programs. Subsequently the model is encoded using the Neptune scripting language and compiled to an object-oriented system for its deployment on distributed systems architecture.