scholarly journals Reflections and Methodological Proposals to Treat the Concept of “Information Precision” in Smart Agriculture Practices

Sensors ◽  
2020 ◽  
Vol 20 (10) ◽  
pp. 2847 ◽  
Author(s):  
Fabrizio Mazzetto ◽  
Raimondo Gallo ◽  
Pasqualina Sacco
Keyword(s):  
Decision Making ◽  
Information Integration ◽  
Production System ◽  
Hierarchical Level ◽  
Technological Basis ◽  
Related Data ◽  
Information Precision ◽  
Smart Agriculture ◽  
Concept Of Information ◽  
Physical And Chemical

Smart Agriculture (SA) is an evolution of Precision Farming (PF). It has technological basis very close to the paradigms of Industry 4.0 (Ind-4.0), so that it is also often referred to as Agriculture 4.0. After the proposal of a brief historical examination that provides a conceptual frame to the above terms, the common aspects of SA and Ind-4.0 are analyzed. These are primarily to be found in the cognitive approaches of Knowledge Management 4.0 (KM4.0, the actual theoretical basis of Ind-4.0), which underlines the need to use Integrated Information Systems (IIS) to manage all the activity areas of any production system. Based upon an infological approach, “raw data” becomes “information” only when useful to (or actually used in) a decision-making process. Thus, an IIS must be always designed according to such a view, and KM4.0 conditions the way of collecting and processing data on farms, together with the “information precision” by which the production system is managed. Such precision needs, on their turn, depend on the hierarchical level and the “Macrodomain of Prevailing Interest” (MPI) related to each decision, where the latter identifies a predominant viewpoint through which a system can be analyzed according to a prevailing purpose. Four main MPIs are here proposed: (1) physical and chemical, (2) biological and ecological, (3) productive and hierarchical, and (4) economic and social. In each MPI, the quality of the knowledge depends on the cognitive level and the maturity of the methodological approaches there achieved. The reliability of information tends to decrease from the first to the fourth MPI; lower the reliability, larger the tolerance margins that a measurement systems must ensure. Some practical examples are then discussed, taking into account some IIS-monitoring solutions of increasing complexity in relation to information integration needs and related data fusion approaches. The analysis concludes with the proposal of new operational indications for the verification and certification of the reliability of the information on the entire decision-making chain.

A Unifying Principle for a Researcher Learning Safety: Reduce Uncertainty!

2018 ◽  
Author(s):  
Camilla Kao ◽  
Russell Furr
Keyword(s):  
Decision Making ◽  
Best Practices ◽  
Mission Statement ◽  
Safety Information ◽  
Health And Safety ◽  
Mission Statements ◽  
Definition Of ◽  
Physical And Chemical

Conveying safety information to researchers is challenging. A list of rules and best practices often is not remembered thoroughly even by individuals who want to remember everything. Researchers in science thinking according to principles: mathematical, physical, and chemical laws; biological paradigms. They use frameworks and logic, rather than memorization, to achieve the bulk of their work. Can safety be taught to researchers in a manner that matches with how they are trained to think? Is there a principle more defined than "Think safety!" that can help researchers make good decisions in situations that are complex, new, and demanding?<div><br></div><div>Effective trainings in other professions can arise from the use of a mission statement that participants internalize as a mental framework or model for future decision-making. We propose that mission statements incorporating the concept of <b>reducing uncertainty</b> could provide such a framework for learning safety. This essay briefly explains the definition of <b>uncertainty</b> in the context of health and safety, discusses the need for an individual to <b>personalize</b> a mission statement in order to internalize it, and connects the idea of <b>greater control</b> over a situation with less uncertainty with respect to safety. The principle of reducing uncertainty might also help <b>non-researchers</b> think about safety. People from all walks of life should be able to understand that more control over their situations provides more protection for them, their colleagues, and the environment.</div>

scholarly journals Nonconscious Cognitive Suffering: Considering Suffering Risks of Embodied Artificial Intelligence

Philosophies ◽  
2019 ◽  
Vol 4 (2) ◽  
pp. 24
Author(s):  
Steven Umbrello ◽  
Stefan Lorenz Sorgner
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Embodied Cognition ◽  
Information Integration ◽  
Physical State ◽  
Conscious State ◽  
Human Cognition ◽  
Machine Consciousness

Strong arguments have been formulated that the computational limits of disembodied artificial intelligence (AI) will, sooner or later, be a problem that needs to be addressed. Similarly, convincing cases for how embodied forms of AI can exceed these limits makes for worthwhile research avenues. This paper discusses how embodied cognition brings with it other forms of information integration and decision-making consequences that typically involve discussions of machine cognition and similarly, machine consciousness. N. Katherine Hayles’s novel conception of nonconscious cognition in her analysis of the human cognition-consciousness connection is discussed in relation to how nonconscious cognition can be envisioned and exacerbated in embodied AI. Similarly, this paper offers a way of understanding the concept of suffering in a way that is different than the conventional sense of attributing it to either a purely physical state or a conscious state, instead of grounding at least a type of suffering in this form of cognition.

Towards a green and fast production system: Integrating life cycle assessment and value stream mapping for decision making

2021 ◽  
Vol 87 ◽  
pp. 106519 ◽  
Author(s):  
Rodrigo Salvador ◽  
Murillo Vetroni Barros ◽  
Giovani Elias Tagliaferro dos Santos ◽  
Karen Godoi van Mierlo ◽  
Cassiano Moro Piekarski ◽  
...  
Keyword(s):  
Decision Making ◽  
Life Cycle Assessment ◽  
Life Cycle ◽  
Production System ◽  
Value Stream Mapping ◽  
Value Stream

scholarly journals A Geometric Framework for Understanding Dynamic Information Integration in Context-Dependent Computation

2021 ◽  
Author(s):  
Xiaohan Zhang ◽  
Shenquan Liu ◽  
Zhe Sage Chen
Keyword(s):  
Decision Making ◽  
Prefrontal Cortex ◽  
Information Integration ◽  
Principal Component ◽  
Population Coding ◽  
Geometric Framework ◽  
Context Dependent ◽  
Activity State ◽  
Low Dimensional ◽  
Context Cues

AbstractPrefrontal cortex plays a prominent role in performing flexible cognitive functions and working memory, yet the underlying computational principle remains poorly understood. Here we trained a rate-based recurrent neural network (RNN) to explore how the context rules are encoded, maintained across seconds-long mnemonic delay, and subsequently used in a context-dependent decision-making task. The trained networks emerged key experimentally observed features in the prefrontal cortex (PFC) of rodent and monkey experiments, such as mixed-selectivity, sparse representations, neuronal sequential activity and rotation dynamics. To uncover the high-dimensional neural dynamical system, we further proposed a geometric framework to quantify and visualize population coding and sensory integration in a temporally-defined manner. We employed dynamic epoch-wise principal component analysis (PCA) to define multiple task-specific subspaces and task-related axes, and computed the angles between task-related axes and these subspaces. In low-dimensional neural representations, the trained RNN first encoded the context cues in a cue-specific subspace, and then maintained the cue information with a stable low-activity state persisting during the delay epoch, and further formed line attractors for sensor integration through low-dimensional neural trajectories to guide decision making. We demonstrated via intensive computer simulations that the geometric manifolds encoding the context information were robust to varying degrees of weight perturbation in both space and time. Overall, our analysis framework provides clear geometric interpretations and quantification of information coding, maintenance and integration, yielding new insight into the computational mechanisms of context-dependent computation.

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.

scholarly journals Parallel Constraint Satisfaction in Memory-Based Decisions

2011 ◽  
Vol 58 (3) ◽  
pp. 180-195 ◽  
Author(s):  
Andreas Glöckner ◽  
Sara D. Hodges
Keyword(s):  
Decision Making ◽  
Constraint Satisfaction ◽  
Information Integration ◽  
Time Pressure ◽  
Human Information Processing ◽  
Decision Task ◽  
Equal Weight ◽  
Decision Strategies ◽  
Simple Heuristics ◽  
Decision Times

Three studies sought to investigate decision strategies in memory-based decisions and to test the predictions of the parallel constraint satisfaction (PCS) model for decision making (Glöckner & Betsch, 2008). Time pressure was manipulated and the model was compared against simple heuristics (take the best and equal weight) and a weighted additive strategy. From PCS we predicted that fast intuitive decision making is based on compensatory information integration and that decision time increases and confidence decreases with increasing inconsistency in the decision task. In line with these predictions we observed a predominant usage of compensatory strategies under all time-pressure conditions and even with decision times as short as 1.7 s. For a substantial number of participants, choices and decision times were best explained by PCS, but there was also evidence for use of simple heuristics. The time-pressure manipulation did not significantly affect decision strategies. Overall, the results highlight intuitive, automatic processes in decision making and support the idea that human information-processing capabilities are less severely bounded than often assumed.

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