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