Results 1 - 10
of
103
Building Multirobot Coalitions Through Automated Task Solution Synthesis -- A group of robots can move to, or push boxes to, specified locations by sharing information when individual robots cannot perform the tasks separately
, 2006
"... This paper presents a reasoning system that enables a group of heterogeneous robots to form coalitions to accomplish a multirobot task using tightly coupled sensor sharing. Our approach, which we call ASyMTRe, maps environmental sensors and perceptual and motor control schemas to the required flow ..."
Abstract
-
Cited by 56 (16 self)
- Add to MetaCart
This paper presents a reasoning system that enables a group of heterogeneous robots to form coalitions to accomplish a multirobot task using tightly coupled sensor sharing. Our approach, which we call ASyMTRe, maps environmental sensors and perceptual and motor control schemas to the required flow of information through the multirobot system, automatically reconfiguring the connections of schemas within and across robots to synthesize valid and efficient multirobot behaviors for accomplishing a multirobot task. We present the centralized anytime ASyMTRe configuration algorithm, proving that the algorithm is correct, and formally addressing issues of completeness and optimality. We then present a distributed version of ASyMTRe, called ASyMTRe-D, which uses communication to enable distributed coalition formation. We validate the centralized approach by applying the ASyMTRe methodology to two application scenarios: multirobot transportation and multirobot box pushing. We then validate the ASyMTRe-D implementation in the multirobot transportation task, illustrating its fault-tolerance capabilities. The advantages of this new approach are that it: 1) enables robots to synthesize new task solutions using fundamentally different combinations of sensors and effectors for different coalition compositions and 2) provides a general mechanism for sharing sensory information across networked robots.
An anytime algorithm for optimal coalition structure generation
- Journal of Artificial Intelligence Research (JAIR
"... Coalition formation is a fundamental type of interaction that involves the creation of coherent groupings of distinct, autonomous, agents in order to efficiently achieve their individual or collective goals. Forming effective coalitions is a major research challenge in the field of multi-agent syste ..."
Abstract
-
Cited by 50 (23 self)
- Add to MetaCart
(Show Context)
Coalition formation is a fundamental type of interaction that involves the creation of coherent groupings of distinct, autonomous, agents in order to efficiently achieve their individual or collective goals. Forming effective coalitions is a major research challenge in the field of multi-agent systems. Central to this endeavour is the problem of determining which of the many possible coalitions to form in order to achieve some goal. This usually requires calculating a value for every possible coalition, known as the coalition value, which indicates how beneficial that coalition would be if it was formed. Once these values are calculated, the agents usually need to find a combination of coalitions, in which every agent belongs to exactly one coalition, and by which the overall outcome of the system is maximized. However, this coalition structure generation problem is extremely challenging due to the number of possible solutions that need to be examined, which grows exponentially with the number of agents involved. To date, therefore, many algorithms have been proposed to solve this problem using different techniques — ranging from dynamic programming, to integer programming, to stochastic search — all of which suffer from major limitations relating to execution time, solution quality, and memory requirements.
Formal modeling and analysis of organizations
- in Proceedings ofthe International Workshop on Organizations in Multi-Agent Systems (OOOP
, 2005
"... Abstract. A new, formal, role-based, framework for modeling and analyzing both real world and artificial organizations is introduced. It exploits static and dynamic properties of the organizational model and includes the (frequently ignored) environment. The transition is described from a generic fr ..."
Abstract
-
Cited by 18 (9 self)
- Add to MetaCart
(Show Context)
Abstract. A new, formal, role-based, framework for modeling and analyzing both real world and artificial organizations is introduced. It exploits static and dynamic properties of the organizational model and includes the (frequently ignored) environment. The transition is described from a generic framework of an organization to its deployed model and to the actual agent allocation. For verification and validation purposes, a set of dedicated techniques is introduced. Moreover, where most models can handle only two or three layered organizational structures, our framework can handle any arbitrary number of organizational layers. Henceforth, real-world organizations can be modeled and analyzed, as illustrated by a case study, within the DEAL project line. 1
On Decentralized Self-Adaptation: Lessons from the Trenches and Challenges for the Future
"... Self-adaptability has been proposed as an effective approach to deal with the increasing complexity, distribution, and dynamicity of modern software systems. Although noteworthy successes have been achieved in many fronts, there is a lack of understanding on how to engineer distributed self-adaptive ..."
Abstract
-
Cited by 16 (9 self)
- Add to MetaCart
(Show Context)
Self-adaptability has been proposed as an effective approach to deal with the increasing complexity, distribution, and dynamicity of modern software systems. Although noteworthy successes have been achieved in many fronts, there is a lack of understanding on how to engineer distributed self-adaptive software systems in which central control is not possible. In this paper, we first describe the key attributes of decentralized self-adaptive systems that set them apart from their centralized counterparts. We illustrate these attributes using two case studies on decentralized self-adaptation. The first case study is an instance of a self-healing system dealing with automated traffic management control. The second case study is an instance of a self-optimizing system that improves the quality of service of a decentralized software system through redeployment of its software components. We generalize the lessons learned from our experiences in the form of a reference model. In light of this model, we present numerous challenges that forms the focus of future research in this area.
Modeling Organizational Performance Indicators
, 2006
"... Performance measurement and analysis is crucial for steering the organization to realizing its strategic and operational goals. Relevant performance indicators and their relationships to goals and activities need to be determined and analyzed. Current organization modeling approaches do not reflect ..."
Abstract
-
Cited by 15 (7 self)
- Add to MetaCart
Performance measurement and analysis is crucial for steering the organization to realizing its strategic and operational goals. Relevant performance indicators and their relationships to goals and activities need to be determined and analyzed. Current organization modeling approaches do not reflect this in an adequate way. This paper attempts to fill the gap by presenting a framework for modeling performance indicators within a general agent-based organization modeling framework.
Multi-Agent Role Allocation: Issues, Approaches, and Multiple Perspectives
- AUTON AGENT MULTI-AGENT SYST
"... In cooperative multi-agent systems, roles are used as a design concept when creating large systems, they are known to facilitate specialization of agents, and they can help to reduce interference in multi-robot domains. The types of tasks that the agents are asked to solve and the communicative capa ..."
Abstract
-
Cited by 11 (0 self)
- Add to MetaCart
In cooperative multi-agent systems, roles are used as a design concept when creating large systems, they are known to facilitate specialization of agents, and they can help to reduce interference in multi-robot domains. The types of tasks that the agents are asked to solve and the communicative capabilities of the agents significantly affect the way roles are used in cooperative multi-agent systems. Along with a discussion of these issues about roles in multi-agent systems, this article compares computational models of the role allocation problem, presents the notion of explicitly versus implicitly defined roles, gives a survey of the methods used to approach role allocation problems, and concludes with a list of open research questions related to roles in multi-agent systems.
Designing institutional multi-agent systems
- of Lecture
"... Abstract. The vision of agents working together on the Internet, in virtual organizations, is one that is increasingly common. However, one of the issues is the regulation of the participating agents and their behaviour. A substantial body of work exists that investigates agent societies and agent o ..."
Abstract
-
Cited by 10 (5 self)
- Add to MetaCart
(Show Context)
Abstract. The vision of agents working together on the Internet, in virtual organizations, is one that is increasingly common. However, one of the issues is the regulation of the participating agents and their behaviour. A substantial body of work exists that investigates agent societies and agent organizations, including work on electronic institutions, such as Islander and Ameli. However, although such work provides concrete tools for specifying and enacting institutions, there is a lack of clear documented guidance to designers who are using these tools. In this paper we describe a methodology for developing an institutional structure for multi agent systems. This methodology captures the knowledge and experience within the Islander group, and integrates it with the Prometheus methodology. 1
Dealing with adaptive multi-agent organizations in the gaia methodology
- In Proceedings AOSE’05, 2005
, 2005
"... Abstract. Changes and adaptations are always necessary after the deployment of a multiagent system (MAS), as well as of any other type of software systems. Some of these changes may be simply perfective and have local impact only. However, adaptive changes to meet changed situations in the operation ..."
Abstract
-
Cited by 10 (2 self)
- Add to MetaCart
(Show Context)
Abstract. Changes and adaptations are always necessary after the deployment of a multiagent system (MAS), as well as of any other type of software systems. Some of these changes may be simply perfective and have local impact only. However, adaptive changes to meet changed situations in the operational environment of the MAS may have global impact on the overall design. In this paper we analyze the issue of continuous design change/adaptation in a MAS organization, and the specific problem of how to properly model/design a MAS so as to make it ready to adaptation. Special attention is paid to the Gaia methodology, whose suitability in dealing with adaptive MAS organization is discussed also with the help of an illustrative application example and analyzed in comparison with a number of different methodologies.
Structural Aspects of the Evaluation of Agent Organizations
- In Coordination, Organizations, Institutions, and Norms in Agent Systems II. Lecture Notes on Computer Science
, 2007
"... ..."
(Show Context)
Curing Robot Autism: A Challenge
"... Almost all robots are autistic; very few humans are. Out of the box, robots generally do not behave correctly in social settings (involving humans, or other agents). Most researchers treat this challenge behaviorally, by superficially tacking task- and domain- specific social behavior onto functioni ..."
Abstract
-
Cited by 7 (2 self)
- Add to MetaCart
(Show Context)
Almost all robots are autistic; very few humans are. Out of the box, robots generally do not behave correctly in social settings (involving humans, or other agents). Most researchers treat this challenge behaviorally, by superficially tacking task- and domain- specific social behavior onto functioning individual robots. These rules are built once, and applied once. In contrast, I posit that we can build better socially-capable robots by relying on general social intelligence building blocks, built into the brains of robots, rather than grafted on per mission: built once, applied everywhere. I challenge the autonomous agents community to synthesize the computational building blocks underlying social intelligence, and to apply them in concrete robot and agent systems. I argue that our field is in a unique position to do this, in that our community intersects with computer science, behavioral and social sciences, robotics, and neuro-science. Thus we can bring to bear a breadth of knowledge and understanding which cannot be matched in other related fields. To lend credibility for our ability to carry out this challenge, I will demonstrate that we have carried out similar tasks in the past (though at a smaller scale). I conclude with a sample of some open questions for research, raised by this challenge.
