Bots with attitude

Bot navigation in many computer games is achieved with static waypoints placed throughout a map. This allows path
finding to be performed by implementing search algorithms to find the optimal path between waypoints using a heuristic
function. This heuristic is usually based on Euclidian distance and terrain. While this type of path finding is effective, it
does not provide for adaptable path finding in a dynamic environment. One concept that promises to achieve adaptive
responses in differing situations in artificial agents is that of emotion. In this paper, we examine the use of positive and
negative feelings, referred to as attitude, in developing a dynamic heuristic for A* that responds by finding paths
between waypoints influenced by a bot’s internal state and its feelings toward objects in the game. Using a traditional
A* heuristic, a bot needing to travel to two goal locations will firstly perform path finding to move to the first goal followed
by path finding for the second goal. Using our dynamic heuristic, the second path finding operation is eliminated as a
path to the second goal via the first goal is calculated. This dynamic heuristic is illustrated in this paper through
experimentation with a bot traversing a map of random waypoints