Abstract
Temporal reasoning constitutes one of the main
topics within the field of Artificial Intelligence. Particularly interesting are interval-based methods, in
which time intervals are treated as basic ontological objects, in opposite to point-based methods,
where time-points are considered as basic. The former approach is more expressive and seems to be
more appropriate for such applications as natural
language analysis or real time processes verification. My research concerns the classical intervalbased logic, namely Halpern-Shoham logic (HS).
In particular, my investigation continues recently
proposed search for well-behaved – i.e., expressive
enough for practical applications and of low computational complexity – HS fragments obtained by
imposing syntactical restrictions on the usage of
propositional connectives in their languages.