The volatility of financial instruments is rarely constant, and usually varies over time. This creates a phenomenon called volatility clustering, where large price movements on one day are followed by similarly large movements on successive days, creating temporal clusters. The GARCH model,...

This paper deals with the automatic detection of slight parameter changes from the analysis of signals generated by nonlinear biological systems. The interest is focused here on investigating particular aspects of the relation between signal analysis and systems dynamics, involving the automatic...

We introduce a two-player model of reinforcement learning with memory. Past actions of an iterated game are stored in a memory and used to determine player’s next action. To examine the behaviour of the model some approximate methods are used and confronted against numerical simulations and...

Occurrence of congestion of packet flow in computer networks is one of the unfavorable problems in packet communication and hence its avoidance should be investigated. We use a neural network model for packet routing control in a computer network proposed in a previous paper by Horiguchi and...

Since the introduction of Reinforcement Learning (RL) in Game Theory, a growing literature is concerned with the theoretical convergence of RL-driven outcomes towards Nash equilibrium. In this paper, we apply this issue to a search-theoretic framework (posted-price market) where sellers are...

We construct and examine a control system with a process called “perception” that selects and completes information received from the system to be controlled. Through a number of basic control tasks, the suggested “perception” paradigm is shown valuable when parts of the information from...