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While artificial intelligence is successful in many applications that cover specific domains, for many commonsense problems there is still a large gap with human performance. Automated sentiment analysis is a typical example: while there are techniques tha ...
Sustaining coherent and engaging narratives requires dialogue or storytelling agents to understand how the personas of speakers or listeners ground the narrative. Specifically, these agents must infer personas of their listeners to produce statements that ...
Several applications require reasoning over autonomously developed ontologies. Initially conceived to explicit the semantics of a certain domain, these ontologies become a powerful tool for supporting business interactions, once heterogeneities have been s ...
We introduce TOQL, a query language for querying time information in ontologies. TOQL is a high level query language that handles ontologies almost like relational databases. Queries are issued as SQL-like statements involving time (i.e., time points or in ...
Text-based games (TBGs) have emerged as useful benchmarks for evaluating progress at the intersection of grounded language understanding and reinforcement learning (RL). Recent work has proposed the use of external knowledge to improve the efficiency of RL ...
This paper presents a multiagent-system for integrating AL-ICE: a real-life, distributed, large-scale particle physics experiment of the LHC project at CERN. The work is concerned with solving the large-scale coordination problem using a distributed constr ...
One of the challenges faced by conversational agents is their inability to identify unstated presumptions of their users' commands, a task trivial for humans due to their common sense. In this paper, we propose a zeroshot commonsense reasoning system for c ...
