In this work, we study the learning of pricing strategies for autonomous Broker Agents in Tariff Markets. We develop an automated Broker Agent that learns its ...
In this work, we study the learning of pricing strategies for autonomous Broker Agents in Tariff Markets. We develop an automated Broker Agent that learns its ...
We investigate the learning of pricing strategies for an autonomous Broker Agent to profitably participate in a Tariff Market. We employ Markov Decision ...
The learning strategy was shown to be much superior to other non learning strategies such as a Random strategy, a Balanced strategy and a Greedy Strategy. ... .
We investigate the learning of pricing strategies for an autonomous Broker Agent to profitably participate in a Tariff Market. We employ Markov Decision ...
We then study the sensitivity of the learned strategies to specific learning parameters and also study the emergent attributes of the market prices and Broker.
This paper presents a novel architecture of electricity agents in smart grid markets. The architecture implements a middleware that allows standard agent ...
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Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence Strategy Learning for Autonomous Agents in Smart Grid Markets.
Oct 22, 2024 · Interestingly, previous work has shown that a Broker Agent can learn its strategy, using Markov Decision Processes (MDPs) and Q-learning, and ...
Reddy, P., Veloso, M.: Strategy learning for autonomous agents in smart grid markets. In: Proceedings of the Twenty-Second International Joint Conference on ...