Sciweavers

Share
ICRA
2005
IEEE

Learning Opportunity Costs in Multi-Robot Market Based Planners

10 years 4 months ago
Learning Opportunity Costs in Multi-Robot Market Based Planners
— Direct human control of multi-robot systems is limited by the cognitive ability of humans to coordinate numerous interacting components. In remote environments, such as those encountered during planetary or ocean exploration, a further limit is imposed by communication bandwidth and delay. Market based planning can give humans a higher-level interface to multi-robot systems in these scenarios. Operators provide high level tasks and attach a reward to the achievement of each task. The robots then trade these tasks through a market based mechanism. The challenge for the system designer is to create bidding algorithms for the robots that yield high overall system performance. Opportunity cost provides a nice basis for such bidding algorithms since it encapsulates all the costs and benefits we are interested in. Unfortunately, computing it can be difficult. We propose a method of learning opportunity costs in market based planners. We provide analytic results in simplified scenarios...
Jeff G. Schneider, David Apfelbaum, Drew Bagnell,
Added 25 Jun 2010
Updated 25 Jun 2010
Type Conference
Year 2005
Where ICRA
Authors Jeff G. Schneider, David Apfelbaum, Drew Bagnell, Reid G. Simmons
Comments (0)
books