AI systems can interact in unexpected ways, sometimes with disastrous consequences. As
AI gets to control more of our world, these interactions will become more common and have …

Newcomblike decision problems have been studied extensively in the decision theory
literature, but they have so far been largely absent in the reinforcement learning literature. In …

As machine learning agents act more autonomously in the world, they will increasingly
interact with each other. Unfortunately, in many social dilemmas like the one-shot Prisoner's …

As machine learning agents act more autonomously in the world, they will increasingly
interact with each other. Unfortunately, in many social dilemmas like the one-shot Prisoner's …

Decision theorists disagree about how instrumentally rational agents, ie, agents trying to
achieve some goal, should behave in so-called Newcomb-like problems, with the main …

Newcomb's problem is a controversial paradox of decision theory. It is easily explained and
easily understood, and there is a strong chance that most of us have actually faced it in …

Intelligent Autonomous Systems (IAS) are highly cognitive, reflective, multitask-able, and
effective in knowledge discovery. Examples of IAS include software systems that are …

Systems with smart autonomy should be capable of exhibiting high-level understanding of
the system beyond their primary actions and their limitations and capacity. They should …

1.1 Abstract Intelligent Autonomous Systems (IAS) reconstruct their perception through
adaptive learning and meet mission objectives. IAS are highly cognitive, rich in knowledge …