Human-Agent Decision-making: Combining Theory and Practice

Extensive work has been conducted both in game theory and logic to model strategic interaction. An important question is whether we can use these theories to design agents for interacting with people? On the one hand, they provide a formal design specification for agent strategies. On the other hand, people do not necessarily adhere to playing in accordance with these strategies, and their behavior is affected by a multitude of social and psychological factors. In this paper we will consider the question of whether strategies implied by theories of strategic behavior can be used by automated agents that interact proficiently with people. We will focus on automated agents that we built that need to interact with people in two negotiation settings: bargaining and deliberation. For bargaining we will study game-theory based equilibrium agents and for argumentation we will discuss logic-based argumentation theory. We will also consider security games and persuasion games and will discuss the benefits of using equilibrium based agents.Comment: In Proceedings TARK 2015, arXiv:1606.0729

Modeling the Psychology of Consumer and Firm Behavior with Behavioral Economics

Marketing is an applied science that tries to explain and influence how firms and consumers actually behave in markets. Marketing models are usually applications of economic theories. These theories are general and produce precise predictions, but they rely on strong assumptions of rationality of consumers and firms. Theories based on rationality limits could prove similarly general and precise, while grounding theories in psychological plausibility and explaining facts which are puzzles for the standard approach. Behavioral economics explores the implications of limits of rationality. The goal is to make economic theories more plausible while maintaining formal power and accurate prediction of field data. This review focuses selectively on six types of models used in behavioral economics that can be applied to marketing. Three of the models generalize consumer preference to allow (1) sensitivity to reference points (and loss-aversion); (2) social preferences toward outcomes of others; and (3) preference for instant gratification (quasi-hyperbolic discounting). The three models are applied to industrial channel bargaining, salesforce compensation, and pricing of virtuous goods such as gym memberships. The other three models generalize the concept of gametheoretic equilibrium, allowing decision makers to make mistakes (quantal response equilibrium), encounter limits on the depth of strategic thinking (cognitive hierarchy), and equilibrate by learning from feedback (self-tuning EWA). These are applied to marketing strategy problems involving differentiated products, competitive entry into large and small markets, and low-price guarantees. The main goal of this selected review is to encourage marketing researchers of all kinds to apply these tools to marketing. Understanding the models and applying them is a technical challenge for marketing modelers, which also requires thoughtful input from psychologists studying details of consumer behavior. As a result, models like these could create a common language for modelers who prize formality and psychologists who prize realism

Flexible Decision Control in an Autonomous Trading Agent

An autonomous trading agent is a complex piece of software that must operate in a competitive economic environment and support a research agenda. We describe the structure of decision processes in the MinneTAC trading agent, focusing on the use of evaluators – configurable, composable modules for data analysis and prediction that are chained together at runtime to support agent decision-making. Through a set of examples, we show how this structure supports sales and procurement decisions, and how those decision processes can be modified in useful ways by changing evaluator configurations. To put this work in context, we also report on results of an informal survey of agent design approaches among the competitors in the Trading Agent Competition for Supply Chain Management (TAC SCM).autonomous trading agent;decision processes

Platform Competition as Network Contestability

Recent research in industrial organisation has investigated the essential place that middlemen have in the networks that make up our global economy. In this paper we attempt to understand how such middlemen compete with each other through a game theoretic analysis using novel techniques from decision-making under ambiguity. We model a purposely abstract and reduced model of one middleman who pro- vides a two-sided platform, mediating surplus-creating interactions between two users. The middleman evaluates uncertain outcomes under positional ambiguity, taking into account the possibility of the emergence of an alternative middleman offering intermediary services to the two users. Surprisingly, we find many situations in which the middleman will purposely extract maximal gains from her position. Only if there is relatively low probability of devastating loss of business under competition, the middleman will adopt a more competitive attitude and extract less from her position.Comment: 23 pages, 3 figure