Dynamic Consistency in Extensive form Decision Problems

In a stimulating paper Piccione and Rubinstein (1997) argued how a decision maker could undertake dynamically inconsistent choices when, in an extensive form decision problem, she exhibits a particular type of imperfect recall named absentmindedness. Such imperfection obtains whenever an information set includes histories along the same decision path. Starting from work focusing on the Absentminded Driver example, and independently developed by Segal (2000) and Dimitri (1999), the main theorem of this paper provides a general result of dynamically consistent choices, valid for a large class of finite extensive form decision problems without nature.

Inductive Game Theory: A Basic Scenario

The aim of this paper is to present the new theory called “inductive game theory”. A paper, published by one of the present authors with A. Matsui, discussed some part of inductive game theory in a specific game. Here, we will give a more developed discourse of the theory. The paper is written to show one entire picture of the theory: From individual raw experiences, short-term memories to long-term memories, inductive derivation of individual views, classification of such views, decision making or modification of behavior based on a view, and repercussion from the modified play in the objective game. We focus on some clear-cut cases, forgetting a lot of possible variants, but will still give a lot of results. In order to show one possible discourse as a whole, we will ask the question of how Nash equilibrium is emerging from the viewpoint of inductive game theory, and will give one answer.

Dynamic optimal fiscal and monetary policy in a business cycle model with income redistribution

An estimation of an optimal program of distortionary taxes, money growth, and borrowing to finance a stream of expenditures based on a real business cycle model in which distribution issues between the rich and poor play a fundamental role in policy decisions.Business cycles ; Monetary policy ; Income distribution

Distributed Task Management in Cyber-Physical Systems: How to Cooperate under Uncertainty?

We consider the problem of task allocation in a network of cyber-physical systems (CPSs). The network can have different states, and the tasks are of different types. The task arrival is stochastic and state-dependent. Every CPS is capable of performing each type of task with some specific state-dependent efficiency. The CPSs have to agree on task allocation prior to knowing about the realized network's state and/or the arrived tasks. We model the problem as a multi-state stochastic cooperative game with state uncertainty. We then use the concept of deterministic equivalence and sequential core to solve the problem. We establish the non-emptiness of the strong sequential core in our designed task allocation game and investigate its characteristics including uniqueness and optimality. Moreover, we prove that in the task allocation game, the strong sequential core is equivalent to Walrasian equilibrium under state uncertainty; consequently, it can be implemented by using the Walras' tatonnement process

Valuation equilibrium

We introduce a new solution concept for games in extensive form with perfect information, valuation equilibrium, which is based on a partition of each player's moves into similarity classes. A valuation of a player'is a real-valued function on the set of her similarity classes. In this equilibrium each player's strategy is optimal in the sense that at each of her nodes, a player chooses a move that belongs to a class with maximum valuation. The valuation of each player is consistent with the strategy profile in the sense that the valuation of a similarity class is the player's expected payoff, given that the path (induced by the strategy profile) intersects the similarity class. The solution concept is applied to decision problems and multi-player extensive form games. It is contrasted with existing solution concepts. The valuation approach is next applied to stopping games, in which non-terminal moves form a single similarity class, and we note that the behaviors obtained echo some biases observed experimentally. Finally, we tentatively suggest a way of endogenizing the similarity partitions in which moves are categorized according to how well they perform relative to the expected equilibrium value, interpreted as the aspiration level

A multi-agent simulation approach to farmland auction markets : repeated games with agents that learn

The focus of this thesis is to better explore and understand the effects of agent interactions, information feedback, and adaptive learning in a repeated game of bidding in farmland auction markets. This thesis will develop a multi-agent model of farm-land auction markets based on data from the Saskatchewan Dark Brown Soil Zone of the Canadian Prairies. Several auction types will be modeled and data will be gathered on land transactions between farm agents to ascertain which auction type (if any) is best suited for farmland markets. Specifically, the model gathers information for 3 types of sealed-bid auctions, and 1 English auction and compares them on the basis of efficiency, price information revelation, stability, and with respect to repeated bidding and agent learning. The effects of auction choice on macro-level indicators, such as farm exits, retirement, financial stability, average productivity, farm size, and participation were unknown at the outset of this thesis because of the complex dynamic nature of the environment. I find that the chosen learning mechanism employed here affects both price and variance of prices in all auctions. I also find that the second-price-sealed-bid auction generates the most perceived surplus, most equitable share of surplus, and also decreases uncertainty in the common-value element of prices. A priori it was believed that auction choice would have an impact on pricing efficiency, price levels, and shares of surplus generated from auctions as predicted by theoretical works. Surprisingly, auction choice does not influence market structure or evolution