DISTRIBUTED COORDINATION OF RESOURCES (DICORE)
THE DICORE PROJECT
Overview
In many domains, there is a need for computational frameworks and
mechanisms that support dynamic coordination of multiple agents toward
achievement of specific global objectives over time. Quite often, the
problem at hand centers on allocation of the resources that each agent
has at its disposal. For example, different manufacturers along a
supply chain have different production capacities and constraints which
must be synchronized over time; various commands in a military
operation must coordinate and time share the use of their assets;
execution of common business processes requires staged participation of
personnel in various organizational units.
To better understand and address such multi-agent coordination problems, we are investigating the following issues: (1) Coordination protocols and policies, (2) Use of projection and look-ahead, and (3) Adaptive decision policies.
Our current research in this direction has been focusing on the development of self-scheduling systems that draw on various aspects of a computational model of the self-organizing behavior of wasp colonies. More specifically, we have been developing the following such self-scheduling systems and algorithms:
- We have been developing wasp-like agents that we call "routing wasps". These "routing wasps" use adaptive decision policies, patterned after the adaptive behavior of real wasps, for the assignment of jobs to multi-purpose machines faced with sequence-dependent setup constraints. On the real-world application of vehicle paintshop scheduling, these "routing wasps" show superior performance to a "real-world" proven multi-agent system for the problem.
- We are also devleoping a stochastic search framework based on the self-organization of dominance hierarchies among wasps in nature. This framework, which we call Wasp beHavior-Inspired STochastic sampLING (WHISTLING), provides a general approach to heuristic-guided stochastic search that utilizes the full potential of the discriminating power of the heuristic for the problem at hand. Underlying WHISTLING is a population of what we call "scheduling wasps" that interact to prioritize the queue of jobs and to search a stochastic neighborhood of the scheduling heuristic.
Recent
Publications
- Cicirello, V.A. and S.F. Smith, "Distributed Coordination of Resources via Wasp-like Agents", The First NASA Goddard/JPL Workshop on Radical Agent Concepts (WRAC), 16-18 January, 2002.
- Cicirello, V.A. and S.F. Smith, "Randomizing Dispatch Scheduling Policies", The 2001 AAAI Fall Symposium: Using Uncertainty Within Computation, 2-4 November, 2001.
- Cicirello, V.A., "A Game-Theoretic Analysis of Multi-Agent Systems for Shop Floor Routing", tech. report CMU-RI-TR-01-28, Robotics Institute, Carnegie Mellon University, September, 2001.
- Cicirello, V.A. and S.F. Smith, "Improved Routing Wasps for Distributed Factory Control", IJCAI-01 Workshop on Artificial Intelligence and Manufacturing, Working Notes, pages 26-32. AAAI SIGMAN, 4-9 August, 2001.
- Cicirello, V.A. and S.F. Smith, "Insect Societies and Manufacturing", IJCAI-01 Workshop on Artificial Intelligence and Manufacturing, Working Notes, pages 33-38. AAAI SIGMAN, 4-9 August, 2001.
- Cicirello, V.A. and S.F. Smith, "Wasp Nests for Self-Configurable Factories", Agents '01, Proceedings of the Fifth International Conference on Autonomous Agents, pages 473-480. ACM Press, May-June, 2001.
- Cicirello, V.A. and S.F. Smith, "Ant Colony Control for Autonomous Decentralized Shop Floor Routing", ISADS-2001: Fifth International Symposium on Autonomous Decentralized Systems, pages 383-390. IEEE Computer Society Press, March, 2001.
Personnel
