Computer Generated Forces (CGF) are software agents which simulate the behaviour of military units or equipment in a distributed interactive simulation environment. Route planning in`realistic' terrain is a critical task for CGF agents, as many of the agent's higher-level goals can only be accomplished if the agent is in the right place at the right time. In this paper we present a new approach to route planning in complex terrains for CGF agents based on searching the space of complete plans. We describe an implementation of these ideas, the salix planner, and report some preliminary results obtained by running the planner on a number of test problems. Our work is also potentially relevant to other applications, e.g. route planning for autonomous vehicles. 1 Route planning in continuous terrains Computer Generated Forces (CGF) are software agents which simulate the behaviour of military units or equipment in a distributed interactive simulation environment. Such systems are becoming increasingly important in areas as diverse as staa training and equipment procurement. For example, CGF agents ooer the potential of dramatically reducing the cost and complexity of mounting training exercises for commanders, with many of the functions carried out by large teams of human controllers replaced by intelligent software agents. These agents must achieve their goals in complex, uncertain and changing environments. Route planning in`realistic' terrain is a critical task for CGF agents, as many of the agent's higher-level goals can only be accomplished if the agent is in the right place at the right time. The problem can be viewed as one of nding a minimum-cost (or low-cost) route between two locations in a digitised map
[1]
Riccardo Poli,et al.
On the Relations Between Search and Evolutionary Algorithms
,
1996
.
[2]
Henri Prade,et al.
Heuristics - intelligent search strategies for computer problem solving, by Judea Pearl. (Reading, Ma: Addison-Wesley, 1984)
,
1986,
Int. J. Intell. Syst..
[3]
Judea Pearl,et al.
Heuristics : intelligent search strategies for computer problem solving
,
1984
.
[4]
Peter Norvig,et al.
Paradigms of Artificial Intelligence Programming: Case Studies in Common Lisp
,
1991
.
[5]
Sumeet Rajput,et al.
Unit Route Planning
,
1994
.
[6]
Nils J. Nilsson,et al.
A Formal Basis for the Heuristic Determination of Minimum Cost Paths
,
1968,
IEEE Trans. Syst. Sci. Cybern..
[7]
Ira Pohl,et al.
The Avoidance of (Relative) Catastrophe, Heuristic Competence, Genuine Dynamic Weighting and Computational Issues in Heuristic Problem Solving
,
1973,
IJCAI.