Search results for " reasoning"
showing 10 items of 357 documents
Performance evaluation of robotic knowledge representation (PERK)
2012
In this paper, we explore some ways in which symbolic knowledge representations have been evaluated in the past and provide some thoughts on what should be considered when applying and evaluating these types of knowledge representations for real-time robotics applications. The emphasis of this paper is that the robotic applications require real-time access to information, which has not been one of the aspects measured in traditional symbolic representation evaluation approaches.
Symbolic and conceptual representation of dynamic scenes: Interpreting situation calculus on conceptual spaces
2001
In (Chella et al. [1,2]) we proposed a framework for the representation of visual knowledge, with particular attention to the analysis and the representation of scenes with moving objects and people. One of our aims is a principled integration of the models developed within the artificial vision community with the propositional knowledge representation systems developed within symbolic AI. In the present note we show how the approach we adopted fits well with the representational choices underlying one of the most popular symbolic formalisms used in cognitive robotics, namely the situation calculus.
Formal operations and postformal reasoning: A replication
1991
The relationship between formal operations and postformal reasoning was examined by using the Shayer (1978) chemicals problem to assess formal operations and the Commons, et al. (1982) four-story problem to measure postformal reasoning. The subjects were 35 undergraduate social science and humanities students. None of the subjects who were classified as concrete operational or transitional on the chemicals task showed postformal reasoning. The hypothesis that full format operations are a necessary condition of post-formal reasoning and the expectation that subjects showing full formal operations are more likely than others to exhibit postformal reasoning was not supported.
Analytic gradients for the coupled-cluster singles, doubles, and triples (CCSDT) model
2002
The first implementation of analytic gradients for the coupled-cluster singles, doubles, triples (CCSDT) model is described. The relevant theoretical expressions are given in a diagrammatic form together with the corresponding algebraic formulas. The computational requirements of CCSDT gradient calculations are discussed and their applicability demonstrated by performing benchmark calculations for molecular geometries with large correlation-consistent basis sets. A statistical analysis of the data reveals that CCSDT and CCSD(T) in most cases perform equally well. The CCSDT calculations thus provide further evidence for the high accuracy of the CCSD(T) approach.
Analytic first and second derivatives for the CCSDT-n (n = 1–3) models: a first step towards the efficient calculation of CCSDT properties
2000
Analytic first and second derivatives of the energy are implemented for closed-shell systems described by the CCSDT-n (n=1, 1b, 2 and 3) and CC3 electron correlation models. A detailed discussion of the computational requirements of these calculations is given, along with diagrammatic formulas for all relevant quantities. The method is applied to calculate the nuclear magnetic shielding of H2O, CO and N2O and the structure and properties of propadienylidene.
Indispensability and Effectiveness of Diagrams in Molecular Biology
2019
Abstract: In this paper I aim to defend a twofold thesis. On one hand, I will support, against Perini (2005), the indispensability of diagrams when structurally complex biomolecules are concerned, since it is not possible to satisfactorily use linguistic-sentential representations at that domain. On the other hand, even when diagrams are dispensable I will defend than they will generally be more effective than other representations in encoding biomolecular knowledge, relying on Kulvicki-Shimojima’s diagrammatic effectiveness thesis. Finally, I will ground many epistemic virtues of biomolecular diagrams (understandability, explanatory power, prediction and hypothesis evaluation) on their cog…
Managing conversation uncertainty in TutorJ
2009
Uncertainty in natural language dialogue is often treated through stochastic models. Some of the authors already presented TutorJ mat is an Intelligent Tutoring System, whose interaction with the user is very intensive, and makes use of both dialogic and graphical modality. When managing the interaction, the system needs to cope with uncertainty due to the understanding of the user's needs and wishes. In this paper we present the extended version of TutorJ, focusing on the new features added to its chatbot module. These features allow to merge deterministic and probabilistic reasoning in dialogue management, and in writing the rules of the system's procedural memory.
Inductive Inference with Procrastination: Back to Definitions
1999
In this paper, we reconsider the definition of procrastinating learning machines. In the original definition of Freivalds and Smith [FS93], constructive ordinals are used to bound mindchanges. We investigate possibility of using arbitrary linearly ordered sets to bound mindchanges in similar way. It turns out that using certain ordered sets it is possible to define inductive inference types different from the previously known ones. We investigate properties of the new inductive inference types and compare them to other types.
Derived sets and inductive inference
1994
The paper deals with using topological concepts in studies of the Gold paradigm of inductive inference. They are — accumulation points, derived sets of order α (α — constructive ordinal) and compactness. Identifiability of a class U of total recursive functions with a bound α on the number of mindchanges implies \(U^{(\alpha + 1)} = \not 0\). This allows to construct counter-examples — recursively enumerable classes of functions showing the proper inclusion between identification types: EXα⊂EXα+1.
Enumerable classes of total recursive functions: Complexity of inductive inference
1994
This paper includes some results on complexity of inductive inference for enumerable classes of total recursive functions, where enumeration is considered in more general meaning than usual recursive enumeration. The complexity is measured as the worst-case mindchange (error) number for the first n functions of the given class. Three generalizations are considered.