@InProceedings{kasenbergscheutz17cdc, author={Daniel Kasenberg and Matthias Scheutz}, title={Interpretable Apprenticeship Learning with Temporal Logic Specifications}, booktitle={Proceedings of the 56th IEEE Conference on Decision and Control (CDC 2017)}, year={2017}, projects={moral}, topics={mc,norm}, synopsis={We consider the problem of inferring temporal logic specifications from agent behavior in stochastic domains. We formulate this as a multi-objective problem and use genetic programming to demonstrate the efficacy of our formluation.}, }

@InProceedings{arnoldetal17aiethics, author = {Thomas Arnold and Daniel Kasenberg and Matthias Scheutz}, title = {Value Alignment or Misalignment -- What Will Keep Systems Accountable?}, booktitle = {{AAAI} Workshop on {AI}, Ethics, and Society}, year = {2017}, projects={norm,mc,plan}, topics={ethics,hri,moral,prag}, synopsis={We present here a critique of a turn toward inverse reinforcement-learning as a way to guarantee ethical AI systems. We argue that a hybrid architecture, which can represent norms explicitly, is necessary for basic social coordination and moral reasoning between people and AI systems.}, }