Theoretical Computer Science
My foundational self-study in TCS aims to deeply understand the limits and capabilities of computation, influencing robust algorithm design and complex system analysis.
- Discrete Mathematics: Exploring combinatorics, graph theory, and number theory for algorithmic problem-solving.
- Automata Theory & Computability: Delving into finite automata, pushdown automata, Turing machines, and the theory of NP-completeness.
- Algorithms & Data Structures: Advanced study of efficient computational methods beyond standard curricula.
- Key Texts: Concrete Mathematics by Graham, Knuth, Patashnik; various resources on advanced algorithms.
AI & Cognitive Systems
A strong focus on the theoretical underpinnings of artificial intelligence, including agent design, decision theory, and the philosophical implications of machine cognition.
- Agent Theory: In-depth study of rational agents, environments, and their interaction models.
- Decision Theory: Understanding formal frameworks for decision-making under uncertainty and risk.
- Cognitive Architectures: Exploring computational models of the human mind and their relevance to AI design.
- Key Texts: Artificial Intelligence: A Modern Approach (AIMA) by Russell & Norvig; seminal papers on cognitive science.
Logic & Philosophy of Computing
Dedicated exploration of raw logic, its application in computing, and the broader philosophical questions arising from advanced technology and intelligence.
- Formal Logic: Delving into propositional, predicate, and modal logics, including proof theory and model theory.
- Philosophy of Mind & AI: Examining consciousness, free will, and the nature of intelligence in both biological and artificial systems.
- Ethical AI Philosophy: Engaging with ethical frameworks, societal impact, and the responsibility of AI developers.
- Key Texts: Works on meta-logic, philosophy of language, and contemporary ethics in technology.
Current Research Focus
My current primary research centers on AI agent formalism and advanced decision theory. I am rigorously studying the theoretical models of intelligent agents and the computational aspects of rational choice. This involves deep dives into optimizing agent behavior in complex, dynamic environments, with a strong emphasis on foundational mathematics.
I am particularly engaged with chapters on utility theory, game theory, and multi-agent systems within the AIMA textbook, supplemented by academic papers on reinforcement learning theory and formal verification of agent behavior. My goal is to bridge theoretical robustness with practical, ethical AI design.