ABSTRACT
Novel predictive modeling analytics techniques with decision trees on competitive models with big data heuristics are presented in brief. Spanning trees are applied to focus on plan goal models that can be processed with splitting agent trees, The chapter is based on agent plan computing where the interaction amongst heterogeneous computing resources is via objects, multiagent AI and agent intelligent languages. Modeling, objectives, and planning issues are examined at an agent planning. Further developing the techniques for model discovery and prediction planning first author developed from the preceding chapters we examine inference decision trees with application to big data areas. Based on the first authors past decade on the preceding chapters, agent computing techniques are applied to present precise decision strategies on multiplayer games with only perfect information between agent pairs on a vector spanning models. We brief on how sparse matrices enable efficient computability on big date heuristics. Predictive analytics on “big data” are presented with new admissibility criteria. Tree computing grammar algebras graphs are a basis for realizing tree goal planning.
