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In this paper, we present the strategy of Agent Madoff, which is aheuristic-based negotiation agent that won 2nd place at the AutomatedNegotiating Agents Competition (ANAC 2017). Agent Madoff is implemented to playthe game Diplomacy, which is a strategic board game that mimics the situationduring World War I. Each player represents a major European power which has tonegotiate with other forces and win possession of a majority supply centers onthe map. We propose a design architecture which consists of 3 components:heuristic module, acceptance strategy and bidding strategy. The heuristicmodule, responsible for evaluating which regions on the graph are more worthy,considers the type of region and the number of supply centers adjacent to theregion and return a utility value for each region on the map. The acceptancestrategy is done on a case-by-case basis according to the type of the order bycalculating the acceptance probability using a composite function. The biddingstrategy adopts a defensive approach aimed to neutralize attacks and resolveconflict moves with other players to minimize our loss on supply centers.

Agent Madoff: A Heuristic-Based Negotiation Agent For The Diplomacy Strategy Game