Epistemic Erotetic Search Scenarios

The aim of this paper is to introduce erotetic search scenarios known from Inferential Erotetic Logic by using the framework of epistemic erotetic logic. The key notions used in this system are those of askability and epistemic erotetic implication. Scenarios are supposed to represent all rational strategies of an agent solving the problem posed by the initial question where the interaction with an external information source is seen as a series of updates of the agent’s knowledge

Riddling and Enculturation: A Glance at the Cerebral Child

This paper attempts to illustrate with concrete data that riddles serve as a didactic device to sharpen the wits of young children. The riddle is described as a verbal routine which adapts the interrogative system of a speech community to purposes of play. Piddles concerning motion or locomotion of animal, machines and toys were collected in a single riddling session, from three Chicano children aged 5-7. The output of these neophyte riddles is discussed in the context of the acquisition and refinement of cognitive categories, and a folk taxonomy focused on the semantic domain of locomotion is suggested. Riddling is viewed as a didactic mechanism conducive to experimentation with received notions of order, and elaboration of novel cognitive orders. In riddlirg, at various stages, children learn to formulate culturally acceptable classifications; to articulate classifications at variance with cultural conventions; and finally to assess language and classification as arbitrary instruments reflecting only partially the continuous texture of experience

Questioning Turing test

The Turing Test (TT) is an experimental paradigm to test for intelligence, where an entity’s intelligence is inferred from its ability, during a text-based conversation, to be recognized as a human by the human judge. The advantage of this paradigm is that it encourages alternative versions of the test to be designed; and it can include any field of human endeavour. However, it has two major problems: (i) it can be passed by an entity that produces uncooperative but human-like responses (Artificial Stupidity); and (ii) it is not sensitive to how the entity produces the conversation (Blockhead). In light of these two problems, I propose a new version of the TT, the Questioning Turing Test (QTT). In the QTT, the task of the entity is not to hold a conversation, but to accomplish an enquiry with as few human-like questions as possible. The job of the human judge is to provide the answers and, like in the TT, to decide whether the entity is human or machine. The QTT has the advantage of parametrising the entity along two further dimensions in addition to ‘human-likeness’: ‘correctness’, evaluating if the entity accomplishes the enquiry; and ‘strategicness’, evaluating how well the entity carries out the enquiry, in terms of the number of questions asked – the fewer, the better. Moreover, in the experimental design of the QTT, the test is not the enquiry per se, but rather the comparison between the performances of humans and machines. The results gained from the QTT show that its experimental design minimises false positives and negatives; and avoids both Artificial Stupidity and Blockhead

Characterizing the Response Space of Questions: data and theory

The main aim of this paper is to provide a characterization of the response space for questions using a taxonomy grounded in a dialogical formal semantics. As a starting point we take the typology for responses in the form of questions provided in \cite{lupginz-jlm}. This work develops a wide coverage taxonomy for question/question sequences observable in corpora including the BNC, CHILDES, and BEE, as well as formal modeling of all the postulated classes. Our aim is to extend this work to cover \emph{all} responses to questions. We present the extended typology of responses to questions based on a corpus studies of BNC, BEE, Maptask and CornellMovie with include 506, 262, 467, and 678 question/response pairs respectively. We compare the data for English with data from Polish using the Spokes corpus (694 question/response pairs). We discuss annotation reliability and disagreement analysis. We sketch how each class can be formalized using a dialogical semantics appropriate for dialogue management

Turingin testi, interrogatiivimalli ja tekoäly

Turingin testi, interrogatiivimalli ja tekoäl

Commonsense Properties from Query Logs and Question Answering Forums

Commonsense knowledge about object properties, human behavior and general concepts is crucial for robust AI applications. However, automatic acquisition of this knowledge is challenging because of sparseness and bias in online sources. This paper presents Quasimodo, a methodology and tool suite for distilling commonsense properties from non-standard web sources. We devise novel ways of tapping into search-engine query logs and QA forums, and combining the resulting candidate assertions with statistical cues from encyclopedias, books and image tags in a corroboration step. Unlike prior work on commonsense knowledge bases, Quasimodo focuses on salient properties that are typically associated with certain objects or concepts. Extensive evaluations, including extrinsic use-case studies, show that Quasimodo provides better coverage than state-of-the-art baselines with comparable quality