The challenge of negotiation in the game of Diplomacy

The game of Diplomacy has been used as a test case for complex automated negotiations for a long time, but to date very few successful negotiation algorithms have been implemented for this game. We have therefore decided to include a Diplomacy tournament within the annual Automated Negotiating Agents Competition (ANAC). In this paper we present the setup and the results of the ANAC 2017 Diplomacy Competition and the ANAC 2018 Diplomacy Challenge. We observe that none of the negotiation algorithms submitted to these two editions have been able to significantly improve the performance over a non-negotiating baseline agent. We analyze these algorithms and discuss why it is so hard to write successful negotiation algorithms for Diplomacy. Finally, we provide experimental evidence that, despite these results, coalition formation and coordination do form essential elements of the game

Automated Negotiation of Smart Contracts for Utility Exchanges between Prosumers in Eco-Industrial Parks

Peer-to-Peer (P2P) Markets of prosumers trading utility surpluses (e.g., heating, cooling, or electric power) is a plausible realization of industrial symbiosis for companies in Eco-Industrial Parks (EIPs) in order to reach significant economic benefits and cut emissions. Through the synergistic co-generation and trading of utilities and industrial services, a P2P Market design makes room for socially desirable behavior despite the inherent selfish nature of each prosumer company. In this paper, a P2P Market prototype for the automated negotiation of utilities between prosumers in an EIP is proposed as a mechanism design to encourage prosumers to participate in trading surpluses. Blockchain transactions and Smart Contracts, combined with Internet of Things (IoTs) technology such as smart meters, are the implementation means to secure that the terms of exchange agreed upon will be automatically enforced. During the simulation of the EIP, each prosumer (represented by a negotiation agent) chooses whether to negotiate with another prosumer or to buy or sell its surpluses to a traditional service provider, such as a main electric power service provider or a gas provider, according to a previously learned policy while considering the context it is immersed in. Utilities between prosumers are exchanged based on a digital currency, the token, which could be readily implemented over Ethereum/Solidity platforms. Smart contract negotiations between prosumers revolve around agreeing (or not) on the price expressed in tokens of a utility profile, given the private and public information available to different parties. Simulation results highlight how automated negotiations allow prosumers to reach higher profits in the P2P Market from trading utility surpluses.Sociedad Argentina de Informática e Investigación Operativ

Automatización de la negociación en un juego de mesa con aproximación a boardgame.io

Una manera de utilizar la IA para simular problemas del mundo real es aplicarla a los juegos de mesa, ya que estos permiten simplificar dicho mundo por medio de unas reglas y/o casillas determinadas, de forma que se puedan abordar en un entorno controlado. Se ha investigado bastante en este campo, pero la mayoría de algoritmos se han desarrollado para juegos de suma cero, en los cuales la suma de las ganancias de unos jugadores es igual a la suma de las pérdidas de los demás, a pesar de que la mayoría de problemas del mundo real son de suma distinta de cero, ya que el beneficio de una parte no suele ser igual a la perdida de la otra, y/o por permitir algún tipo de negociación. En este proyecto se desarrolla un juego de mesa de suma distinta de cero que permite negociar, y se automatiza dicha negociación en base a las posibles situaciones que se pueden dar en el juego, programando para ello un Sistema Experto Basado en Reglas con CLIPS. Además, se realiza una aproximación teórica a boardgame.io de forma que se indican los pasos que se deben seguir si se quiere implementar el juego desarrollado en la herramienta, además de lo que hay que tener en cuenta si se quiere añadir la solución de la automatización de la negociación al juego una vez éste se haya implementado.A way to use AI to simulate real world problems is to apply it to board games due to the fact that they allow to simplify this world by some determined rules, in a way that can be approached in a controlled environment. Research in this field has been made but most of the algorithms have been developed for zero-sum games, in which the sum of gains of some players is equal to the sum of losses of the rest of players, despite most of real world problems are non zero-sum, because the benefit of one part is not usually the same as the losses of the other and/or for allowing some type of negotiation. In this project a non-zero sum game with negotiations is developed and this negotiation is automated in base of the possible situations that can be possible in the game, programming for it a CLIPS Rule Based Expert System. Also, a theoretical approach to boardgame.io is made in a way that steps to follow for implementing the game developed in the tool is given, apart from what has to be taken into account if implementing the solution of automation of negotiations is intended once the game is implemented.Grado en Ingeniería Informátic

Automated negotiations for general game playing

In this paper we present a new algorithm for negotiations in non-zero-sum games. Although games have been studied extensively, most game playing algorithms have been developed under the assumption that players do not communicate. Many real-world problems, however, can be modeled as non-zero-sum games in which players may mutually benefit if they coordinate their actions, which requires negotiation. The field of Automated Negotiations is another important topic in AI, but in this field one usually assumes that utility functions have explicit expressions and can therefore be calculated easily. Traditional approaches do not apply to domains in which the utility values are instead determined by the rules of a complex game. In this paper we aim to bridge the gap between General Game Playing and Automated Negotiations. Our algorithm is an adaptation of Monte Carlo Tree Search that allows players to negotiate. It is completely domain-independent in the sense that it is not tailored to any specific game. It can be applied to any non-zero-sum game, provided that its rules are described in Game Description Language

Automated Negotiations for General Game Playing

[EN]In this paper we present a new algorithm for negotiations in non-zero-sum games. Although games have been studied extensively, most game playing algorithms have been developed under the assumption that players do not communicate. Many real-world problems, however, can be modeled as non-zero-sum games in which players may mutually benefit if they coordinate their actions, which requires negotiation. The field of Automated Negotiations is another important topic in AI, but in this field one usually assumes that utility functions have explicit expressions and can therefore be calculated easily. Traditional approaches do not apply to domains in which the utility values are instead determined by the rules of a complex game. In this paper we aim to bridge the gap between General Game Playing and Automated Negotiations. Our algorithm is an adaptation of Monte Carlo Tree Search that allows players to negotiate. It is completely domain-independent in the sense that it is not tailored to any specific game. It can be applied to any non-zero-sum game, provided that its rules are described in Game Description LanguagePeer reviewe