Sotiris Batsakis
Papers
1
Total Citations
7
H-Index
1
About
Sotiris Batsakis is a leading researcher in knowledge representation and reasoning, with a primary focus on qualitative spatial and temporal reasoning. His work addresses the challenge of encoding and reasoning with qualitative theories—such as natural language expressions about time and space—using formal computational frameworks. His most-cited paper, "A Generalised Approach for Encoding and Reasoning with Qualitative Theories in Answer Set Programming" (2020, 7 citations), introduces a novel method for representing over 40 qualitative calculi in Answer Set Programming, enabling efficient and scalable reasoning across diverse domains. This contribution is pivotal for advancing AI systems that require human-like understanding of spatial and temporal relationships. Batsakis’s research has significant implications for areas like robotics, geographic information systems, and natural language processing, where qualitative reasoning is essential. His work stands out for its generality and practical applicability, making complex qualitative theories accessible to automated reasoning tools. With a growing citation impact, Batsakis continues to shape the field of qualitative reasoning, offering foundational techniques that bridge symbolic AI and real-world problem-solving.
Research Focus
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Top Papers
- 1