This work introduces a geometric analysis of the problem of inverse reinforcement learning (IRL) and proposes a formal guarantee for the optimality of the reward function, obtained from the empirical data. The authors also provide the sample complexity for their proposed l1-regularized Support Vector Machine formulation. In general, this is an interesting work with a significant contribution to the theoretical aspect of the inverse reinforcement learning problem. However, there are a few concerns that need to be addressed: Major: 1. The paper does not define the problem as a stand-alone question in the field. The problem formulation heavily relies on the previous work by Ng & Russel (2000) and is written only as a follow up to this work.

The TARK conference (Theoretical Aspects of Rationality and Knowledge) is a conference that aims to bring together researchers from a wide variety of fields, including computer science, artificial intelligence, game theory, decision theory, philosophy, logic, linguistics, and cognitive science. Its goal is to further our understanding of interdisciplinary issues involving reasoning about rationality and knowledge. Previous conferences have been held biennially around the world since 1986, on the initiative of Joe Halpern (Cornell University). Topics of interest include, but are not limited to, semantic models for knowledge, belief, awareness and uncertainty, bounded rationality and resource-bounded reasoning, commonsense epistemic reasoning, epistemic logic, epistemic game theory, knowledge and action, applications of reasoning about knowledge and other mental states, belief revision, computational social choice, algorithmic game theory, and foundations of multi-agent systems. Information about TARK, including conference proceedings, is available at http://www.tark.org/ These proceedings contain the papers that have been accepted for presentation at the Nineteenth Conference on Theoretical Aspects of Rationality and Knowledge (TARK 2023), held between June 28 and June 30, 2023, at the University of Oxford, United Kingdom. The conference website can be found at https://sites.google.com/view/tark-2023

Over millions of years, humans have adapted mysterious pathways to evolve the art of communication. It all started with gossiping which later enabled us to communicate and convey our messages to other human beings in an effective manner using sound. To narrow it down there are two major factors involved in boosting human evolution, one is language and the other is machines.The industrial revolution made a huge impact on every ecosystem. Alongside humans, machines are also evolving, in the early 80s we had to operate machines mechanically, and later when electronic machines we being designed we started using switches, and now we have to program machines. But only handful of specialized computer scientists can design and program these complicated machines.

The TARK conference (Theoretical Aspects of Rationality and Knowledge) is a biannual conference that aims to bring together researchers from a wide variety of fields, including computer science, artificial intelligence, game theory, decision theory, philosophy, logic, linguistics, and cognitive science. Its goal is to further our understanding of interdisciplinary issues involving reasoning about rationality and knowledge. Topics of interest include, but are not limited to, semantic models for knowledge, belief, awareness and uncertainty, bounded rationality and resource-bounded reasoning, commonsense epistemic reasoning, epistemic logic, epistemic game theory, knowledge and action, applications of reasoning about knowledge and other mental states, belief revision, and foundations of multi-agent systems. These proceedings contain the papers that have been accepted for presentation at the Eighteenth Conference on Theoretical Aspects of Rationality and Knowledge (TARK 2021), held between June 25 and June 27, 2021, at Tsinghua University at Beijing, China.