We present a strategy for automatic negotiation that takes the same approach as computer programs that play games such as chess; we build the game tree. For every offer we look at every counteroffer, every counteroffer to each of them, and so on. The strategy then selects the counteroffer that has the largest expected payoff. A number of problems arise that are unique to using this strategy for negotiation. These include uncertainty in the opponent's goals, the fact that a bad move can penalize both players, and moves that are continuous, as opposed to discrete. We show how the standard methods of building the tree and evaluating the results were adapted to this environment. Notes: 14 Pages