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http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.101.2375
Knowledge can be exchanged among the agents by using a combination of facts, rules and commands transfers. This framework has been partially implemented and has been proven to be a viable implementation for multi-agent approaches for decision support in stock trading.
https://www.researchgate.net/publication/244957107_A_multi-agent_system_framework_for_decision_support_in_Stock_Trading
This framework has been partially implemented and has been proven to be a viable implementation for multi-agent approaches for decision support in stock trading.
http://www2.cs.siu.edu/~rahimi/papers/11-.pdf
exchange markets, while this paper puts forward a multi-agent system that is capable of providing a base for a comprehensive Artificial Stock Market (ASM). Based on the authors’ knowledge, currently, there exists no multi-agent based system that entirely and expansively model stock exchange process from the initiation to completion of a request.
https://www.academia.edu/19665812/A_multi-agent_system_framework_for_decision_support_in_Stock_Trading
A multi-agent system framework for decision support in Stock Trading
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.198.5244
Based on the requirement analysis, this paper presents a framework for a Multi-Agent System for Stock Trading (MASST). The key issues it addresses include gathering and integrating diverse information sources with collaborating agents, and providing decision-making for investors in the stock market.
https://www.semanticscholar.org/paper/A-multi-agent-framework-for-stock-trading-Rahimi-Tatikunta/9f9e78206965d87394ab15016cafbde83ecb2d76
The multi-agent paradigm is the framework for implementation of the system. The properties of intelligent software agents meet the characteristics of the actors on the trading floor and provide capabilities for efficient distributed computing.
https://core.ac.uk/display/20696039
Knowledge can be exchanged among the agents by using a combination of facts, rules and commands transfers. This framework has been partially implemented and has been proven to be a viable implementation for multi-agent approaches for decision support in stock tradingAuthor: Yuan Luo, Darryl N. Davis and Kecheng Liu
https://core.ac.uk/display/21518785
Based on the requirement analysis, this paper presents a framework for a Multi-Agent System for Stock Trading (MASST). The key issues it addresses include gathering and integrating diverse information sources with collaborating agents, and providing decision-making for investors in the stock market.Author: Darryl Davis, Yuan Luo and Kecheng Liu
https://pdfs.semanticscholar.org/d484/a3a6f81b4fd9ec3f41472b17207f9e70f73e.pdf
There have been several multi-agent system designs for supporting information gathering and decision making in stock trading area such as the system suggested by Hu and Lio which supports dynamic information and knowledge exchange among the cooperating agents (Luo & Liu, 2002).
https://www.researchgate.net/publication/221465347_A_Multi-agent_Q-learning_Framework_for_Optimizing_Stock_Trading_Systems
This paper presents a reinforcement learning framework for stock trading systems. Trading system parameters are optimized by Qlearning algorithm and neural networks are adopted for value approximation. In this framework, cooperative multiple agents are used to efficiently...
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