Multi-agent Behavior-Based Policy Transfer

2016 ◽  
pp. 181-197 ◽  
Author(s):  
Sabre Didi ◽  
Geoff Nitschke
Keyword(s):  
Policy Transfer ◽  
Agent Behavior ◽  
Multi Agent ◽  
Behavior Based

Modular Representations of Cognitive Phenomena in AI, Psychology and Neuroscience

2011 ◽  
pp. 66-89 ◽  
Author(s):  
Joanna J. Bryson
Keyword(s):  
Artificial Intelligence ◽  
Cognitive Science ◽  
Conscious Experience ◽  
Modular Representations ◽  
Domain Specific ◽  
Massive Modularity ◽  
Multi Agent ◽  
Individual Domain ◽  
Behavior Based

Many architectures of mind assume some form of modularity, but what is meant by the term ‘module’? This chapter creates a framework for understanding current modularity research in three subdisciplines of cognitive science: psychology, artificial intelligence (AI), and neuroscience. This framework starts from the distinction between horizontal modules that support all expressed behaviors vs. vertical modules that support individual domain-specific capacities. The framework is used to discuss innateness, automaticity, compositionality, representations, massive modularity, behavior-based and multi-agent AI systems, and correspondence to physiological neurosystems. There is also a brief discussion of the relevance of modularity to conscious experience.

The Effectiveness of Transferring Multi-Agent Behaviors From a Learning Environment in the Presence of Synthetic Social Structures

2005 ◽  
Author(s):  
Keith Garfield ◽  
Annie Wu ◽  
Mehmet Onal ◽  
Britt Crawford ◽  
Adam Campbell ◽  
...  
Keyword(s):  
Learning Environment ◽  
Autonomous Vehicles ◽  
Social Structures ◽  
Agent Behavior ◽  
The Social ◽  
Multi Agent ◽  
Group Members ◽  
The Common ◽  
Primary Focus ◽  
The Impact

The diverse behavior representation schemes and learning paradigms being investigated within the robotics community share the common feature that successful deployment of agents requires that behaviors developed in a learning environment are successfully applied to a range of unfamiliar and potentially more complex operational environments. The intent of our research is to develop insight into the factors facilitating successful transfer of behaviors to the operational environments. We present experimental results investigating the effects of several factors for a simulated swarm of autonomous vehicles. Our primary focus is on the impact of Synthetic Social Structures, which are guidelines directing the interactions between agents, much like social behaviors direct interactions between group members in the human and animal world. The social structure implemented is a dominance hierarchy, which has been shown previously to facilitate negotiation between agents. The goal of this investigation is to investigate mechanisms adding robustness to agent behavior.

Multi-agent and driving behavior based rear-end collision alarm modeling and simulating

2010 ◽  
Vol 18 (8) ◽  
pp. 1092-1103 ◽  
Author(s):  
Jun Liang ◽  
Long Chen ◽  
Xian-yi Cheng ◽  
Xian-bo Chen
Keyword(s):  
Driving Behavior ◽  
Multi Agent ◽  
Behavior Based

Multi-Agent Societies for Collaborative Interaction

1996 ◽  
Vol 40 (15) ◽  
pp. 762-766 ◽  
Author(s):  
Robin R. Penner
Keyword(s):  
Process Management ◽  
Social Structures ◽  
Management Systems ◽  
Interface Model ◽  
Agent Architecture ◽  
Situated Action ◽  
Agent Behavior ◽  
Agent Societies ◽  
Multi Agent ◽  
Collaborative Interaction

The application of a multi-agent architecture to the design and operation of automated process management systems is proving to be a fruitful method of facilitating human-system collaboration. The agent architecture we are developing is intended to be applied in environments where humans and automated systems jointly perform information intensive tasks, and is based on an organization of multiple agents, where both human and software agents are integrated members in groups akin to human societies. Important features of our architecture include an organization based on social structures, a user interface model based on a collaborative interaction metaphors, and a situated action paradigm for agent behavior.

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