Goal Management in Organizations: A Markov Decision Process (MDP) Approach

Goal management is the process of recognizing or inferring goals of individual team members; abandoning goals that are no longer relevant; identifying and resolving conflicts among goals; and prioritizing goals consistently for optimal team collaboration and effective operations. A Markov decision process (MDP) approach is employed to maximize the probability of achieving the primary goals (a subset of all goals). The authors seek to address the computational adequacy of an MDP as a planning model by introducing novel problem domain-specific heuristic evaluation functions (HEF) to aid the search process. They employ the optimal AO* search and two suboptimal greedy search algorithms to solve the MDP problem. A comparison of these algorithms to the dynamic programming algorithm shows that computational complexity can be reduced substantially. In addition, they recognize that embedded in the MDP solution there are a number of different action sequences by which a team's goals can be realized. That is, in achieving the aforementioned optimality criterion, they identify alternate sequences for accomplishing the primary goals. Prepared in cooperation with Aptima, Inc., Woburn, MA. The original document contains color images.