Simon's Bounded Rationality. Origins and use in economic theory

The paper aims to show how Simon's notion of bounded rationality should be interpreted in the light of its connection with artificial intelligence. This connection points out that bounded rationality is a highly structured concept, and sheds light on several implications of Simon's general views on rationality. Finally, offering three paradigmatic examples, the artic1e presents the view that recent approaches, which refer to Simon's heterodox theory, only partially accept the teachings of their inspirer, splitting bounded rationality from the context of artificl al intelligence.

Intelligent escalation and the principle of relativity

Escalation is the fact that in a game (for instance in an auction), the agents play forever. The $0,1$-game is an extremely simple infinite game with intelligent agents in which escalation arises. It shows at the light of research on cognitive psychology the difference between intelligence (algorithmic mind) and rationality (algorithmic and reflective mind) in decision processes. It also shows that depending on the point of view (inside or outside) the rationality of the agent may change which is proposed to be called the principle of relativity.Comment: arXiv admin note: substantial text overlap with arXiv:1306.228

Zero-Intelligence Trading without Resampling

This paper studies the consequences of removing the resampling assumption from the zero-intelligence trading model in Gode and Sunder (1993). We obtain three results. First, individual rationality is no longer sufficient to attain allocative effciency in a continuous double auction; hence, the rules of the market matter. Second, the allocative effciency of the continuous double auction is higher than for other sequential protocols both with or without resampling. Third, compared to zero intelligence, the effect of learning on allocative effciency is sharply positive without resampling and mildly negative with resampling.

Individual Rationality and Market Efficiency

The demonstration by Smith [1962] that prices and allocations quickly converge to the competitive equilibrium in the continuous double auction (CDA) was one of the first – and remains one of the most important results in experimental economics. His initial experiment, subsequent market experiments, and models of price adjustment and exchange have added considerably to our knowledge of how markets reach equilibrium, and how they respond to disruptions. Perhaps the best known model of exchange in CDA market experiments is the random behavior in the “zero-intelligence” (ZI) model by Gode and Sunder [1993]. They conclude that even without trader rationality the CDA generates efficient allocations and “convergence of transaction prices to the proximity of the theoretical equilibrium price,” provided only that agents meet their budget constraints. We demonstrate that – by any reasonable measure – prices don’t converge in their simulations. Their budget constraint requires that a buyer’s currency never exceeds her value for the commodity, which is an unnatural restriction. Their conclusion that market efficiency results from the structure of the CDA independent of traders’ profit seeking behavior rests on their claim that the constraints that they impose are a part of the market institution, but this is not so. We show that they in effect impose individual rationality, which is an aspect of agents' behavior. Researchers on learning in markets have been misled by their interpretation of the ZI simulations, with deleterious effects on the debate on market adjustment processes.Bounded rationality; double auction; exchange economy; experimental economics; market experiment; "zero intelligence" model

Ants don't have friends: thoughts on socially intelligent agents

The question what is an agent? has been under dis cussion for many years. However, a consensus exists that the term 'agent' only makes sense in a multi-agent context - namely if there are at least two agents and assuming interaction and or communication between the agents. Agent research is generally done fairly independently in dfferent research areas, separated by the nature of the agents - natural or articial. This paper presents some thoughts on agency and sociality. Social intelligence is studied in the context of human style forms of social behaviour. Issues like embodiment, believability, rationality, social understanding,and different levels of social organisation and control are discussed

An Evolutionary Model of Bounded Rationality and Intelligence

Background: Most economic theories are based on the premise that individuals maximize their own self-interest and correctly incorporate the structure of their environment into all decisions, thanks to human intelligence. The influence of this paradigm goes far beyond academia–it underlies current macroeconomic and monetary policies, and is also an integral part of existing financial regulations. However, there is mounting empirical and experimental evidence, including the recent financial crisis, suggesting that humans do not always behave rationally, but often make seemingly random and suboptimal decisions. Methods and Findings: Here we propose to reconcile these contradictory perspectives by developing a simple binary-choice model that takes evolutionary consequences of decisions into account as well as the role of intelligence, which we define as any ability of an individual to increase its genetic success. If no intelligence is present, our model produces results consistent with prior literature and shows that risks that are independent across individuals in a generation generally lead to risk-neutral behaviors, but that risks that are correlated across a generation can lead to behaviors such as risk aversion, loss aversion, probability matching, and randomization. When intelligence is present the nature of risk also matters, and we show that even when risks are independent, either risk-neutral behavior or probability matching will occur depending upon the cost of intelligence in terms of reproductive success. In the case of correlated risks, we derive an implicit formula that shows how intelligence can emerge via selection, why it may be bounded, and how such bounds typically imply the coexistence of multiple levels and types of intelligence as a reflection of varying environmental conditions. Conclusions: Rational economic behavior in which individuals maximize their own self interest is only one of many possible types of behavior that arise from natural selection. The key to understanding which types of behavior are more likely to survive is how behavior affects reproductive success in a given population’s environment. From this perspective, intelligence is naturally defined as behavior that increases the probability of reproductive success, and bounds on rationality are determined by physiological and environmental constraints.Massachusetts Institute of Technology. Laboratory for Financial Engineerin