Tell Me More! Towards Implicit User Intention Understanding of Language Model Driven Agents

Current language model-driven agents often lack mechanisms for effective user participation, which is crucial given the vagueness commonly found in user instructions. Although adept at devising strategies and performing tasks, these agents struggle with seeking clarification and grasping precise user intentions. To bridge this gap, we introduce Intention-in-Interaction (IN3), a novel benchmark designed to inspect users' implicit intentions through explicit queries. Next, we propose the incorporation of model experts as the upstream in agent designs to enhance user-agent interaction. Employing IN3, we empirically train Mistral-Interact, a powerful model that proactively assesses task vagueness, inquires user intentions, and refines them into actionable goals before starting downstream agent task execution. Integrating it into the XAgent framework, we comprehensively evaluate the enhanced agent system regarding user instruction understanding and execution, revealing that our approach notably excels at identifying vague user tasks, recovering and summarizing critical missing information, setting precise and necessary agent execution goals, and minimizing redundant tool usage, thus boosting overall efficiency. All the data and codes are released.Comment: 26 pages, 5 tables, 6 figure

Risk-sharing and probabilistic network structure

This paper studies the impact of a probabilistic risk-sharing network structure on the optimal portfolio composition. We show that, even assuming identical agents, we are able to differentiate their optimal risk-choice once we assume the link-structure defining their relationship probabilistic. In particular, the final agent's portfolio composition is function of his location in the network. If we assume positive asset-correlation coefficients, the relative location of a player in the graph influences his risk-behaviour as much as those of his direct and indirect partners in a not-straightforward way. We analyse also two potential "centrality measures" able to select the key-player in the risk-sharing network. The findings may help to select the "central" agent in a risk-sharing community and to forecast the risk-exposure of the players. Finally, this paper may explain natural differences between identical rational agents' choices emerging in a probabilistic network setup

Trading behavior and excess volatility in toy markets

We study the relation between the trading behavior of agents and volatility in toy markets of adaptive inductively rational agents. We show that excess volatility, in such simplified markets, arises as a consequence of {\em i)} the neglect of market impact implicit in price taking behavior and of {\em ii)} excessive reactivity of agents. These issues are dealt with in detail in the simple case without public information. We also derive, for the general case, the critical learning rate above which trading behavior leads to turbulent dynamics of the market.Comment: 14 pages, 4 figures, minor change

Conformity-Driven Agents Support Ordered Phases in the Spatial Public Goods Game

We investigate the spatial Public Goods Game in the presence of fitness-driven and conformity-driven agents. This framework usually considers only the former type of agents, i.e., agents that tend to imitate the strategy of their fittest neighbors. However, whenever we study social systems, the evolution of a population might be affected also by social behaviors as conformism, stubbornness, altruism, and selfishness. Although the term evolution can assume different meanings depending on the considered domain, here it corresponds to the set of processes that lead a system towards an equilibrium or a steady-state. We map fitness to the agents' payoff so that richer agents are those most imitated by fitness-driven agents, while conformity-driven agents tend to imitate the strategy assumed by the majority of their neighbors. Numerical simulations aim to identify the nature of the transition, on varying the amount of the relative density of conformity-driven agents in the population, and to study the nature of related equilibria. Remarkably, we find that conformism generally fosters ordered cooperative phases and may also lead to bistable behaviors.Comment: 13 pages, 5 figure

The Emergence of Norms via Contextual Agreements in Open Societies

This paper explores the emergence of norms in agents' societies when agents play multiple -even incompatible- roles in their social contexts simultaneously, and have limited interaction ranges. Specifically, this article proposes two reinforcement learning methods for agents to compute agreements on strategies for using common resources to perform joint tasks. The computation of norms by considering agents' playing multiple roles in their social contexts has not been studied before. To make the problem even more realistic for open societies, we do not assume that agents share knowledge on their common resources. So, they have to compute semantic agreements towards performing their joint actions. %The paper reports on an empirical study of whether and how efficiently societies of agents converge to norms, exploring the proposed social learning processes w.r.t. different society sizes, and the ways agents are connected. The results reported are very encouraging, regarding the speed of the learning process as well as the convergence rate, even in quite complex settings

Continuum time limit and stationary states of the Minority Game

We discuss in detail the derivation of stochastic differential equations for the continuum time limit of the Minority Game. We show that all properties of the Minority Game can be understood by a careful theoretical analysis of such equations. In particular, i) we confirm that the stationary state properties are given by the ground state configurations of a disordered (soft) spin system; ii) we derive the full stationary state distribution; iii) we characterize the dependence on initial conditions in the symmetric phase and iv) we clarify the behavior of the system as a function of the learning rate. This leaves us with a complete and coherent picture of the collective behavior of the Minority Game. Strikingly we find that the temperature like parameter which is introduced in the choice behavior of individual agents turns out to play the role, at the collective level, of the inverse of a thermodynamic temperature.Comment: Revised version (several new results added). 12 pages, 5 figure

On the Micro-foundations of Money: The Capitol Hill Baby-Sitting Co-op.

This paper contributes to the micro-foundation of money in centralized markets with idiosyncratic uncertainty. It shows existence of stationary monetary equilibria and ensures that there is an optimum quantity of money. The rational solution of our model is compared with actual behavior in a laboratory experiment. The experiment gives support to the theoretical approach.micro foundations of money; optimal quantity of money