Utilizing the well-known Ultimatum Game, this note presents the following phenomenon. If we start with simple stimulus-response agents, learning through naive reinforcement, and then grant them some introspective capabilities, we get outcomes that are not closer but farther away from the fully...

In this paper we provide a brief introduction to the literature on agent-based financial modelling and, more specifically, artificial stock market modelling. In the selective literature review two broad categories of artificial stock market models are discussed: models based on hard-wired rules...

The construction of automatic Financial Trading Systems (FTSs) is a subject of research of high interest for both academic environment and financial one due to the potential promises by self-learning methodologies and by the increasing power of actual computers. In this paper we consider...

Reinforcement learning (RL) is a state or action value based machine learning method which solves large-scale multi-stage decision problems such as Markov Decision Process (MDP) and Semi-Markov Decision Process (SMDP) problems. We minimize the makespan of flow shop scheduling problems with an RL...

This article investigates how neurons can use metabolic cost to facilitate learning at a population level. Although decision-making by individual neurons has been extensively studied, questions regarding how neurons should behave to cooperate effectively remain largely unaddressed. Under...

Self-organization, especially in the framework of embodiment in biologically inspired robots, allows the acquisition of behavioral primitives by autonomous robots themselves. However, it is an open question how self-organization of basic motor primitives and goal-orientation can be combined,...

Classical conditioning (conventionally modeled as correlation-based learning) and operant conditioning (conventionally modeled as reinforcement learning or reward-based learning) have been found in biological systems. Evidence shows that these two mechanisms strongly involve learning about...

Business simulators are powerful tools for both supporting the decision-making process of business managers as well as for business education. An example is SIMBA (SIMulator for Business Administration), a powerful simulator which is currently used as a web-based platform for business education...

Probability estimation is an essential cognitive function in perception, motor control, and decision making. Many studies have shown that when making decisions in a stochastic operant conditioning task, people and animals behave as if they underestimatethe probability of rare events. It is...

This discussion paper resulted in a publication in the <I>Journal of Economic Dynamics & Control</I>. Volume 33(11), pp. 1912-1928.<P> This paper formalizes the idea that more hedging instruments may destabilize markets when traders are heterogeneous and adapt their behavior according to experience based...</p></i>