This paper asks how a player should exploit knowledge that their opponent in a repeated game is using a no-regret learning algorithm. Prior work has studied this question in Bayesian settings, such as when the learning player is a buyer and the rational player is a seller. This question extends the ideas to a non-Bayesian setting. In general, the rational player can guarantee the first-mover Stackelberg utility in the game. That is, being rational against a no-regret learner is worth at least as much as going first in a Stackelberg game.

In this paper, we explore the susceptibility of the independent Q-learning algorithms (a classical and widely used multi-agent reinforcement learning method) to strategic manipulation of sophisticated opponents in normal-form games played repeatedly. We quantify how much strategically sophisticated agents can exploit naive Q-learners if they know the opponents' Q-learning algorithm. To this end, we formulate the strategic actors' interactions as a stochastic game (whose state encompasses Q-function estimates of the Q-learners) as if the Q-learning algorithms are the underlying dynamical system. We also present a quantization-based approximation scheme to tackle the continuum state space and analyze its performance for two competing strategic actors and a single strategic actor both analytically and numerically.

Studies forecast that AI will boost profitability by an average of 38% by the year 2035. If an AI program interpreted this data, the result would be conclusive: Artificial intelligence is quickly becoming one of the economy's sharpest competitive edges. According to McKinsey & Company, just 47% of executives report embedding AI into one business process, and only 21% report implementing AI in multiple ways. While the technology is progressing at historically unprecedented rates, the majority of enterprises still face either barriers to entry or difficulty determining next steps. Whether a company is beginning its journey with AI, or ready to take the next measured step, it's essential to conduct a comprehensive AI audit.

It's no secret that Big Data and artificial intelligence are taking over a lot of industries, whether it is corporate banking, retail or travel and hospitality. It's a topic that either terrifies companies who feel unprepared for this innovation or excited by its incredible possibilities. Yet, with every opportunity comes certain risks. With Big Data, there are numerous aspects to consider, and companies looking to implement Big Data need to be aware of possible challenges. Here, we'll discuss them in detail.