Jun Kiniwa

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 can show the prices will reach an equilibrium by iterating buy and sell operations. We introduce a framework of protocols 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). So far, we have just considered such a model in a synchronous environment. We, however, cannot represent the velocity of circulation of money in the synchronous system. In other words, we cannot distinguish the different speed of money movement if every operation is synchronized. Thus, we develop an asynchronous model which enables us to generalize the theory of price stabilization in networks. Finally, we execute simulation experiments and investigate the influence of network features on the velocity of money.

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.

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 can show the prices will reach an equilibrium by iterating buy and sell operations. First, we present a framework of protocols 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). In this situation, the number of bidding agents is uncertain if several selling agents exist in the neighborhood. Just like a usual auction, each agent has a value of goods and decides a bidding price from it. We apply equilibrium bidding strategies for the first-price auction and the second-price auction to our framework. called a first-price protocol and a second-price protocol, respectively. Though the best bidding strategies are derived from Bayesian-Nash equilibrium, which assumes the certain number of bidding agents in contrast to our model. So we consider an expected number of bidding agents by assuming their values are uniformly distributed over (0,1). Next, we examine whether or not the prices reach an equilibrium for the protocols. Finally, we show the second-price protocol outperforms the first-price protocol from a fund-spreading point of view. Our results have an application to a monetary policy and a management using agent information.

We consider a simple network model for economic agents where each can buy goods in the neighborhood. Their prices may be initially distinct in any node. However, by assuming some rules on new prices, we show that the distinct prices will reach an equilibrium price by iterating buy and sell operations. First, we present a protocol model in which each agent always bids at some rate in the difference between his own price and the lowest price in the neighborhood. Next, we show that the equilibrium price can be derived from the total funds and the total goods for any network. This confirms that the inflation / deflation occurs due to the increment / decrement of funds as long as the quantity of goods is constant. Finally, we consider how injected funds spread in a path network because sufficient funds of each agent drive him to buy goods. This is a monetary policy for deflation. A set of recurrences lead to the price of goods at each node at any time. Then, we compare two injections with half funds and single injection. It turns out the former is better than the latter from a fund-spreading point of view, and thus it has an application to a monetary policy and a strategic management based on the information of each agent.

We propose a space-time Hotelling model that introduces a unit size of the vertical time axis in the classical Hotelling unit interval model. The proposed model allows explicit consideration of the probability that a consumer arrives at a retail store up to time t to purchase goods. The proposed model is useful in a variety of retailing problems. We briefly demonstrate an application of the proposed model to retail competition in a duopoly.