5,755 research outputs found
Crawford-Sobel meet Lloyd-Max on the grid
The main contribution of this work is twofold. First, we apply, for the first
time, a framework borrowed from economics to a problem in the smart grid
namely, the design of signaling schemes between a consumer and an electricity
aggregator when these have non-aligned objectives. The consumer's objective is
to meet its need in terms of power and send a request (a message) to the
aggregator which does not correspond, in general, to its actual need. The
aggregator, which receives this request, not only wants to satisfy it but also
wants to manage the cost induced by the residential electricity distribution
network. Second, we establish connections between the exploited framework and
the quantization problem. Although the model assumed for the payoff functions
for the consumer and aggregator is quite simple, it allows one to extract
insights of practical interest from the analysis conducted. This allows us to
establish a direct connection with quantization, and more importantly, to open
a much more general challenge for source and channel coding.Comment: ICASSP 2014, 5 page
Decentralization of Multiagent Policies by Learning What to Communicate
Effective communication is required for teams of robots to solve
sophisticated collaborative tasks. In practice it is typical for both the
encoding and semantics of communication to be manually defined by an expert;
this is true regardless of whether the behaviors themselves are bespoke,
optimization based, or learned. We present an agent architecture and training
methodology using neural networks to learn task-oriented communication
semantics based on the example of a communication-unaware expert policy. A
perimeter defense game illustrates the system's ability to handle dynamically
changing numbers of agents and its graceful degradation in performance as
communication constraints are tightened or the expert's observability
assumptions are broken.Comment: 7 page
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