木庭 淳

We consider a multiagent network model consisting of nodes and edges as cities and their links to neighbors, respectively. Each network node has an agent and priced goods and the agent can buy or sell goods in the neighborhood. Though every node may not have an equal price, we show the prices will reach an equilibrium by iterating buy and sell operations. First, we present a protocol model in which each buying agent makes a bid to the lowest priced goods in the neighborhood and each selling agent selects the highest bid, if any. Second, we derive a sufficient condition which stabilizes price in our model. We also show the equilibrium price can be derived from the total funds and the total goods for any network. This is a special case of the Fisher's quantity equation, thus we can confirm the correctness of our model. We then examine the best bidding strategy is available to our protocol. Third, we analyze stabilization time for path and cycle networks. Finally, we perform simulation experiments for estimating the stabilization time, the number of bidders and the effects of spreading funds. Our model is suitable for investigating the effects of network topologies on price stabilization.

In 1997, a minority game (MG) was proposed as a non-cooperative iterated game with an odd population of agents who make bids whether to buy or sell. Since then, many variants of the MG have been proposed. However, the common disadvantage in their characteristics is to ignore the past actions beyond a constant memory. So it is difficult to simulate actual payoffs of agents if the past price behavior has a significant influence on the current decision. In this paper we present a new variant of the MG, called an asset value game (AG), and its extension, called an extended asset value game (ExAG). In the AG, since every agent aims to decrease the mean acquisition cost of his asset, he automatically takes the past actions into consideration. The AG, however, is too simple to reproduce the complete market dynamics, that is, there may be some time lag between the price and his action. So we further consider the ExAG by using probabilistic actions, and compare them by simulation. © Springer-Verlag Berlin Heidelberg 2013.

A minority game (MG) is a non-cooperative iterated game with an odd population agents who make bids whether to buy or sell. Based on the framework of MG, several kinds of games have been proposed. However, the common disadvantage nu their characteristics is to neglect past actions. So WC present a new variant of the MG, called an asset value game (AG), in which every agent aims to decrease a mean asset value, that is. an acquisition cost averaged through the past actions. The AG, however, is too simple to reproduce the complete market dynamics. So we further consider an improvement of AG, called an extended asset value game (ExAG), and investigate their features and obtain some results by simulation.

A non-cooperative iterated multiagent game, called a minority game, and its variations have been extensively studied in this decade. To increase its market similarity, a $-game was presented by observing the current and the next agent's payoffs. However, since the $-game is defined as an offline game, it is difficult to simulate it in practice. So we propose a new online version of the $-game, called a lazy $-game, and analyze the price behavior of the game. First, we reveal the condition of a bubble phenomenon in the lazy $-game. Next, we investigate the price behavior in the lazy $-game and show that there are some upper/lower bounds of the price as long as both the buyers group and the sellers group are nonempty. Then, we consider the similarity between the lazy $-game and the $-game. Finally, we present some simulation results. (C) 2009 Elsevier B.V. All rights reserved.