Fuzzy inductive reasoning, expectation formation and the behavior of security prices

Tay, Nicholas S. P.; Linn, Scott C.

doi:10.1016/s0165-1889(00)00029-4

Cited by 53 publications

(26 citation statements)

References 25 publications

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“…One important recent development in agent-based social simulation has occurred in the use of natural language (Lindström, 1998;He et al, 2002;Tay and Linn, 2001). People frequently and routinely use natural language or linguistic values, such as high, low, and so on, to describe their perception, demands, expectations, and decisions.…”

Section: Behavioral Complexitymentioning

confidence: 99%

“…Tay and Linn (2001) made progress in this direction by using the genetic-fuzzy classifier system (GFCS) to model traders' adaptive behavior in an artificial stock market. Tay and Linn (2001) provided a good illustration of the non-equivalence between the acknowledgement of the cognitive constraint and the assumption of simple agents. It is well-known that the human mind is notoriously bad at intuitively comprehending exponential growth.…”

Section: Behavioral Complexitymentioning

confidence: 99%

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On the Selection of Adaptive Algorithms in ABM: A Computational-Equivalence Approach

Chen

Tai

2006

Comput Econ

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Abstract. Agent-based Methodology (ABM) is becoming indispensable for the interdisciplinary study of social and economic complex adaptive systems. The essence of ABM lies in the notion of autonomous agents whose behavior may evolve endogenously and can generate and mimic the corresponding complex system dynamics that the ABM is studying. Over the past decade, many Computational Intelligence (CI) methods have been applied to the design of autonomous agents, in particular, their adaptive schemes. This design issue is non-trivial since the chosen adaptive schemes usually have a profound impact on the generated system dynamics. Robert Lucas, one of the most influential modern economic theorists, has suggested using laboratories with human agents, also known as Experimental Economics, to help solve the selection issue. While this is a promising approach, laboratories used in the current experimental economics are not computationally equipped to meet the demands of the selection task. This paper attempts to materialize Lucas' suggestion by establishing a laboratory where human subjects are equipped with the computational power that satisfies the computational equivalence condition.

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Section: Behavioral Complexitymentioning

confidence: 99%

Section: Behavioral Complexitymentioning

confidence: 99%

On the Selection of Adaptive Algorithms in ABM: A Computational-Equivalence Approach

Chen

Tai

2006

Comput Econ

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“…Several shapes can be used for defining membership functions of fuzzy sets; among them are triangular, trapezoidal, Gaussian, and s-curve [48,50]. Triangular fuzzy membership function, because of its simple arithmetic operations, is usually considered for modeling uncertain processing times.…”

Section: Applied Fuzzy Setmentioning

confidence: 99%

Toward learning autonomous pallets by using fuzzy rules, applied in a Conwip system

Mehrsai

Karimi

Scholz‐Reiter

2012

Int J Adv Manuf Technol

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Nowadays, material planning and control strategies are becoming continuously complex tasks spanning from individual plants to logistic networks. In fact, this is the consequence of increasing intricacy in product variants and their respective convolution in networks' structures. Customers ask for specific products with individual characteristics that force companies for more clever performances by more flexibility. For doing so, the existing planning and control systems, which work based on central monitoring and controlling, show some limitations for organizing every operation on time or in the right time. Therefore, in the recent decade, a great attention is put on decentralized control and, to some extent, autonomy. This paper tries to investigate the possibility of combining this new research paradigm with existing strategies in production logistics, in order to improve material handling and control task according to material flow criteria. To show this, an exemplary plant after decoupling point out of a logistic network is considered for simulation and analysis. This combines Conwip system with learning autonomous pallets' concept in a discrete event simulation model. Several decentralized control scenarios are experimented and compared together. Here, the learn methodology is brought to pallets based on fuzzy rules and advantage of closed loop systems.

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“…The most prominent example of the latter category is the Santa Fe ASM model developed by Arthur et al (1997); also see, e.g. Beltratti and Margarita (1992), Lettau (1997), LeBaron (2000), Tay and Linn (2001). See Ramanauskas (2009) for a general discussion about agent-based fi nancial modelling and the above-mentioned models.…”

Section: Description Of the Asm Modelmentioning

confidence: 99%

Building an Artificial Stock Market Populated by Reinforcement‐learning Agents

Rutkauskas

Ramanauskas

2009

Journal of Business Economics and Management

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Abstract. In this paper we propose an artifi cial stock market model based on interaction of heterogeneous agents whose forward-looking behaviour is driven by the reinforcement-learning algorithm combined with some evolutionary selection mechanism. We use the model for the analysis of market self-regulation abilities, market effi ciency and determinants of emergent properties of the fi nancial market. Distinctive and novel features of the model include strong emphasis on the economic content of individual decision-making, application of the Q-learning algorithm for driving individual behaviour, and rich market setup. Along with that a parallel version of the model is presented, which is mainly based on research of current changes in the market, as well as on search of newly emerged consistent patterns, and which has been repeatedly used for optimal decisions' search experiments in various capital markets.

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Fuzzy inductive reasoning, expectation formation and the behavior of security prices

Cited by 53 publications

References 25 publications

On the Selection of Adaptive Algorithms in ABM: A Computational-Equivalence Approach

On the Selection of Adaptive Algorithms in ABM: A Computational-Equivalence Approach

Toward learning autonomous pallets by using fuzzy rules, applied in a Conwip system

Building an Artificial Stock Market Populated by Reinforcement‐learning Agents

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