EXPLAINABLE AND SCALABLE PLANNING WITH PROBABILISTIC TEMPORAL LOGIC SPECIFICATIONS THE OBJECTIVE OF THIS PROPOSAL IS TO DEVELOP THEORY ALGORITHMS AND DEMONSTRATIONS FOR FORMAL SPECIFICATIONS AND AUTOMATED SYNTHESIS AND LEARNING OF AUTONOMY PROTOCOLS FOR MISSION RESOURCE AND CONTINGENCY MANAGEMENT. WE PARTITION THE EFFORT INTO THREE THRUSTS: (I) COMPOSITIONAL AND HIERARCHICAL SYNTHESIS -- DEVELOP METHODS FOR AUTOMATED SYNTHESIS FROM PROBABILISTIC TEMPORAL LOGIC SPECIFICATIONS. (II) INTERPRETABLE PLANS -- DEVELOP AUTOMATA-LEARNING METHODS TO SYNTHESIZE HUMAN-INTERPRETABLE PLANS FOR PRACTICALLY INFINITE-STATE SYSTEMS. (III) EXPLAINABLE FEEDBACK -- IN CASES IN WHICH THERE IS NO ACCEPTABLE PLAN DEVELOP EXPLANATIONS OF THE CORE REASONS IN TERMS UNDERSTANDABLE BY HUMANS. ALL THREE THRUSTS ADDRESS SCALABILITY EXPLICITLY THROUGH A SERIES OF ALGORITHMIC AND ARCHITECTURAL MEASURES. IN PARALLEL WITH THE TECHNICAL THRUSTS WE WILL DEMONSTRATE AND SPECIALIZE OUR ALGORITHMS IN A CASE STUDY ON HUMAN SPACEFLIGHT OPERATIONS. WE DESIGNED OUR TECHNICAL THRUSTS TO BALANCE THEIR GENERAL APPLICABILITY AND THEIR IMPACT AND TIMELINESS FOR HUMAN SPACEFLIGHT OPERATIONS. OUR EFFORT INTRODUCES A PARADIGM SHIFT IN THE PLANNING-EXECUTION (AND RE-PLANNING) LOOP BY ADDRESSING A NUMBER OF THESE CHALLENGES. OUR EMPHASIS PARTICULARLY ON UNAMBIGUOUS FORMAL SPECIFICATIONS AND COMPILATION OF EXECUTABLE CONTROL SOFTWARE WITH PROVABLE GUARANTEES AND SYSTEMATIC SENSITIVITY ANALYSIS DIFFUSES THE CRITICAL CONCERN OF RELIABILITY THROUGHOUT THE PLANNING-EXECUTION LOOP. FURTHERMORE THE PROPOSED ALGORITHMS WILL INCORPORATE MODELS WITH STOCHASTIC AS WELL AS NONDETERMINISTIC UNCERTAINTIES AND RICH SPECIFICATIONS WITH TEMPORAL AND LOGICAL RELATIONS AS WELL AS PROBABILISTIC AND REAL-TIME MODALITIES AS NEEDED. INTEGRATED PLANNING FOR THE COUPLED FUNCTIONS INTRODUCES POSSIBILITIES FOR SYSTEM-LEVEL OPTIMIZATION E.G. IN PERFORMANCE WEIGHTS AND OVERALL COST. FINALLY THE PROPOSED ALGORITHMIC AND ARCHITECTURAL ADVANCES WILL IMPROVE NOT ONLY THE SCALABILITY OF THE RESULTING SYNTHESIS ALGORITHMS BUT ALSO THEIR INTERPRETABILITY BY AND EXPLAINABILITY TO THE CREW AND DESIGNERS.