NEXCEL, a deductive spreadsheet

2007 ◽  
Vol 22 (3) ◽  
pp. 221-236 ◽  
Author(s):  
ILIANO CERVESATO
Keyword(s):  
Decision Making ◽  
Cognitive Psychology ◽  
Numerical Calculation ◽  
Computer Users ◽  
Formal Training ◽  
Logical Inference ◽  
Microsoft Excel ◽  
Symbolic Data ◽  
Logical Rules ◽  
Spreadsheet Application

AbstractUsability and usefulness have made the spreadsheet one of the most successful computing applications of all times: millions rely on it every day for anything from typing grocery lists to developing multimillion-dollar budgets. One thing spreadsheets are not very good at is manipulating the symbolic data and helping users make decisions based on them. By tapping into recent research in Logic Programming, Databases and Cognitive Psychology, we propose a deductive extension to the spreadsheet paradigm that precisely addresses this issue. The accompanying tool, which we call NEXCEL, is intended as an automated assistant for the daily reasoning and decision-making needs of computer users, in the same way as a spreadsheet application such as Microsoft Excel assists them every day with simple and complex calculations. Users without formal training in Logic or even Computer Science can interactively define logical rules in the same simple way as they define formulas in Excel. NEXCEL immediately evaluates these rules, thereby returning lists of values that satisfy them, again just like with numerical formulas. The deductive component is seamlessly integrated into the traditional spreadsheet so that a user not only still has access to the usual functionalities but is also able to use them as part of the logical inference and, dually, to embed deductive steps in a numerical calculation.

scholarly journals Reasoning Through the Disjunctive Syllogism in Monkeys

2021 ◽  
Vol 32 (2) ◽  
pp. 292-300
Author(s):  
Stephen Ferrigno ◽  
Yiyun Huang ◽  
Jessica F. Cantlon
Keyword(s):  
Decision Making ◽  
Food Choice ◽  
Human Learning ◽  
Choice Task ◽  
Logical Inference ◽  
Critical Aspect ◽  
Disjunctive Syllogism ◽  
Symbolic Thought ◽  
Dependent Relation ◽  
Nonhuman Animals

The capacity for logical inference is a critical aspect of human learning, reasoning, and decision-making. One important logical inference is the disjunctive syllogism: given A or B, if not A, then B. Although the explicit formation of this logic requires symbolic thought, previous work has shown that nonhuman animals are capable of reasoning by exclusion, one aspect of the disjunctive syllogism (e.g., not A = avoid empty). However, it is unknown whether nonhuman animals are capable of the deductive aspects of a disjunctive syllogism (the dependent relation between A and B and the inference that “if not A, then B” must be true). Here, we used a food-choice task to test whether monkeys can reason through an entire disjunctive syllogism. Our results show that monkeys do have this capacity. Therefore, the capacity is not unique to humans and does not require language.

Errors in Surgical Neuropathology and the Influence of Cognitive Biases: The Psychology of Intelligence Analysis

2006 ◽  
Vol 130 (5) ◽  
pp. 613-616 ◽  
Author(s):  
Roger E. McLendon
Keyword(s):  
Decision Making ◽  
Cognitive Psychology ◽  
Medical Decision Making ◽  
Cognitive Biases ◽  
Correct Diagnosis ◽  
Data Sources ◽  
Medical Decision ◽  
Intelligence Analysis ◽  
First Impression ◽  
Decision Making Processes

Abstract Context.—A significant difficulty that pathologists encounter in arriving at a correct diagnosis is related to the way information from various sources is processed and assimilated in context. Objective.—These issues are addressed by the science of cognitive psychology. Although cognitive biases are the focus of a number of studies on medical decision making, few if any focus on the visual sciences. Data Sources.—A recent publication authored by Richards Heuer, Jr, The Psychology of Intelligence Analysis, directly addresses many of the cognitive biases faced by neuropathologists and anatomic pathologists in general. These biases include visual anticipation, first impression, and established mindsets and subconsciously influence our critical decision-making processes. Conclusions.—The book points out that while biases are an inherent property of cognition, the influence of such biases can be recognized and the effects blunted.

scholarly journals A Semantic Web-based Representation of Human-logical Inference for Solving Bongard Problems

2020 ◽  
Vol 26 (10) ◽  
pp. 1343-1363
Author(s):  
Jisha Maniamma ◽  
Hiroaki Wagatsuma
Keyword(s):  
Decision Making ◽  
Semantic Web ◽  
Description Logic ◽  
Logical Reasoning ◽  
Hierarchical Level ◽  
Logical Inference ◽  
Learning Abilities ◽  
Web Based ◽  
Wide Range ◽  
Target Frame

Bongard Problems (BPs) are a set of 100 visual puzzles introduced by M. M. Bongard in the mid-1960s. BPs have been established as benchmark puzzles for understanding the human context-based learning abilities to solve ill- posed problems. The puzzle requires the logical explanation as the answer to distinct two classes of figures from redundant options, which can be obtained by a thinking process to alternatively change the target frame (hierarchical level of analogy) of thinking from a wide range concept networks as D. R. Hofstadter suggested. Some minor research results to solve a limited set of BPs have reported based a single architecture accompanied with probabilistic approaches; however the central problem on BP's difficulties is the requirement of flexible changes of the target frame, therefore non-hierarchical cluster analyses does not provide the essential solution and hierarchical probabilistic models needs to include unnecessary levels for learning from the beginning to prevent a prompt decision making. We hypothesized that logical reasoning process with limited numbers of meta-data descriptions realizes the sophisticated and prompt decision-making and the performance is validated by using BPs. In this study, a semantic web-based hierarchical model to solve BPs was proposed as the minimum and transparent system to mimic human-logical inference process in solving of BPs by using the Description Logic (DL) with assertions on concepts (TBox) and individuals (ABox). Our results demonstrated that the proposed model not only provided individual solutions as a BP solver, but also proved the correctness of Hofstadter's idea as the flexible frame with concept networks for BPs in our actual implementation, which no one has ever achieved. This fact will open the new horizon for theories for designing of logical reasoning systems especially for critical judgments and serious decision-making as expert humans do in a transparent and descriptive way of why they judged in that manner.

An Early Framework for a Cognitive Neuroscience of Visual Aesthetics

2021 ◽  
pp. 3-7
Author(s):  
Anjan Chatterjee
Keyword(s):  
Decision Making ◽  
Cognitive Psychology ◽  
Visual Processing ◽  
Motor System ◽  
Testing Hypotheses ◽  
Aesthetic Experiences ◽  
Cognitive Domains ◽  
Visual Aesthetics ◽  
The Rich

In the early 2000s, no framework within which to investigate the biology of aesthetics had been articulated. The author believes that a componential framework, as was common in cognitive psychology, applied to neuroaesthetics made sense. Such frameworks were commonly applied to complex cognitive domains, such as in language, emotion processing, or visual processing research. As such, the author proposes a “box and arrow” model which incorporated levels of visual processing, emotions, attention, and decision-making. The advantage of such a framework is that specific experiments could be placed in the context of testing hypotheses of parts of a larger system deployed for aesthetic processing. The framework has held up well over the years, although the author believes he did not sufficiently emphasize the role of the motor system and the rich contribution of semantics in aesthetic experiences.

scholarly journals Critical Computation: Digital Automata and General Artificial Thinking

2019 ◽  
Vol 36 (2) ◽  
pp. 89-121 ◽  
Author(s):  
Luciana Parisi
Keyword(s):  
Decision Making ◽  
Information Processing ◽  
Inductive Method ◽  
Logical Thinking ◽  
Logical Inference ◽  
Critical Reasoning ◽  
Learning From Data ◽  
Human Thinking ◽  
Computational Systems ◽  
Adaptive Practice

As machines have become increasingly smart and have entangled human thinking with artificial intelligences, it seems no longer possible to distinguish among levels of decision-making that occur in the newly formed space between critical reasoning, logical inference and sheer calculation. Since the 1980s, computational systems of information processing have evolved to include not only deductive methods of decision, whereby results are already implicated in their premises, but have crucially shifted towards an adaptive practice of learning from data, an inductive method of retrieving information from the environment and establishing general premises. This shift in logical methods of decision-making does not simply concern technical apparatuses, but is a symptom of a transformation in logical thinking activated with and through machines. This article discusses the pioneering work of Katherine Hayles, whose study of the cybernetic and computational infrastructures of our culture particularly clarifies this epistemological transformation of thinking in relation to machines.

Cognitive Science of Tourism Experiences

2022 ◽  
pp. 1-21
Author(s):  
Noel Scott ◽  
Ana Claudia Campos
Keyword(s):  
Decision Making ◽  
Cognitive Psychology ◽  
Cognitive Science ◽  
Theoretical Discussion ◽  
Tourism Research ◽  
Behavioural Approach ◽  
Tourism Experience ◽  
Emotion Memory ◽  
The Way

While other disciplinary approaches such as sociology and anthropology are important, this chapter introduces a cognitivist psychology approach to experience research. Such theoretical discussion may seem of little practical use, but the chapter argues that it is fundamental to understanding how and why experiences are created. The chapter applies theory and concepts from cognitive science (cognitive psychology and neuroscience) in the study of tourism experiences. This provides a different psychological paradigm to the behavioural approach currently in use in much research. The chapter describes the scope of cognitive psychology and neuroscience, its main concepts of cognitive psychology (perception, attention, emotion, memory, consciousness, learning), and their neuronal basis (neuroscience). These concepts are then applied in three topic areas related to tourism experiences: decision making, emotion, and attention. Several applications to tourism experience research are noted. Finally, the chapter discusses the way cognitive psychology concepts can be used in tourism research.

scholarly journals Enhanced Knowledge Graph Embedding by Jointly Learning Soft Rules and Facts

Algorithms ◽  
2019 ◽  
Vol 12 (12) ◽  
pp. 265 ◽  
Author(s):  
Jindou Zhang ◽  
Jing Li
Keyword(s):  
Link Prediction ◽  
State Of The Art ◽  
Background Knowledge ◽  
Background Information ◽  
Knowledge Graph ◽  
Logical Inference ◽  
Training Algorithm ◽  
First Order ◽  
Forward Chaining ◽  
Logical Rules

Combining first order logic rules with a Knowledge Graph (KG) embedding model has recently gained increasing attention, as rules introduce rich background information. Among such studies, models equipped with soft rules, which are extracted with certain confidences, achieve state-of-the-art performance. However, the existing methods either cannot support the transitivity and composition rules or take soft rules as regularization terms to constrain derived facts, which is incapable of encoding the logical background knowledge about facts contained in soft rules. In addition, previous works performed one time logical inference over rules to generate valid groundings for modeling rules, ignoring forward chaining inference, which can further generate more valid groundings to better model rules. To these ends, this paper proposes Soft Logical rules enhanced Embedding (SoLE), a novel KG embedding model equipped with a joint training algorithm over soft rules and KG facts to inject the logical background knowledge of rules into embeddings, as well as forward chaining inference over rules. Evaluations on Freebase and DBpedia show that SoLE not only achieves improvements of 11.6%/5.9% in Mean Reciprocal Rank (MRR) and 18.4%/15.9% in HITS@1 compared to the model on which SoLE is based, but also significantly and consistently outperforms the state-of-the-art baselines in the link prediction task.

Development and Implementation of The Dispersant Observation Job Aid

1999 ◽  
Vol 1999 (1) ◽  
pp. 1015-1018
Author(s):  
Edwin A. Levine
Keyword(s):  
Decision Making ◽  
Open Water ◽  
Formal Training ◽  
Decision Making Process ◽  
Regional Policies ◽  
Actual Application ◽  
Unified Command ◽  
Aerial Observation ◽  
The Individual ◽  
Job Aid

ABSTRACT The Job Aid is a field guide for dispersant observers after formal training. Individuals are prepared to observe applications by different platforms and able to competently describe their observations back to a command structure for decision making. The observer is not a controller or spotter for the actual application operation. For field durability it is formatted as bound 5″×7″plastic-coated cards. This Job Aid focuses on supporting the “Observation of Aerial Applications of Dispersants” training. This training imparts the ability to identify oil, describe its characteristics, and make recommendations back to the Federal On-Scene Coordinator (FOSC) concerning future dispersant actions. The observer's recommendations to the Unified Command (UC) may range from “continue operations,” “modify operations,” or “cease operations.”, The training is based upon the supposition that the decision to use dispersants has already been made. The training does not attempt to cover the decision making process. It is incumbent on the individual to be familiar with the local and regional policies regarding use of dispersants and subsequent monitoring requirements. This job aid should be used in conjunction with the “Open Water Oil Identification Job Aid for Aerial Observation” to help describe the surface oil.

Weather Forecasting by Humans—Heuristics and Decision Making

2004 ◽  
Vol 19 (6) ◽  
pp. 1115-1126 ◽  
Author(s):  
Charles A. Doswell
Keyword(s):  
Decision Making ◽  
Cognitive Psychology ◽  
Multidisciplinary Approach ◽  
Weather Forecasting ◽  
Judgment And Decision Making ◽  
Human Cognition ◽  
Weather Forecasts ◽  
Weather Forecasters ◽  
Insight Into ◽  
Considerable Insight

Abstract The decision-making literature contains considerable information about how humans approach tasks involving uncertainty using heuristics. Although there is some reason to believe that weather forecasters are not identical in all respects to the typical subjects used in judgment and decision-making studies, there also is evidence that weather forecasters are not so different that the existing understanding of human cognition as it relates to making decisions is entirely inapplicable to weather forecasters. Accordingly, some aspects of cognition and decision making are reviewed and considered in terms of how they apply to human weather forecasters, including biases introduced by heuristics. Considerable insight into human forecasting could be gained by applying available studies of the cognitive psychology of decision making. What few studies exist that have used weather forecasters as subjects suggest that further work might well be productive in terms of helping to guide the improvement of weather forecasts by humans. It is concluded that a multidisciplinary approach, involving disciplines outside of meteorology, needs to be developed and supported if there is to be a future role for humans in forecasting the weather.

The 33rd Sir Frederick Bartlett Lecture Cognitive neuropsychiatry and delusional belief

2007 ◽  
Vol 60 (8) ◽  
pp. 1041-1062 ◽  
Author(s):  
Max Coltheart
Keyword(s):  
Decision Making ◽  
Cognitive Psychology ◽  
Theory Of Mind ◽  
Cognitive Process ◽  
Belief Formation ◽  
Normal Operation ◽  
High Level ◽  
Delusional Belief

Cognitive neuropsychiatry is a new field of cognitive psychology which seeks to learn more about the normal operation of high-level aspects of cognition such as belief formation, reasoning, decision making, theory of mind, and pragmatics by studying people in whom such processes are abnormal. So far, the high-level cognitive process most widely studied in cognitive neuropsychiatry has been belief formation, investigated by examining people with delusional beliefs. This paper describes some of the forms of delusional belief that have been examined from this perspective and offers a general two-deficit cognitive-neuropsychiatric account of delusional belief.

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