scholarly journals Synthesizing Best-effort Strategies under Multiple Environment Specifications

2021 ◽  
Author(s):  
Benjamin Aminof ◽  
Giuseppe De Giacomo ◽  
Alessio Lomuscio ◽  
Aniello Murano ◽  
Sasha Rubin
Keyword(s):  
Solution Concept ◽  
Important Case ◽  
Synthesis Problem ◽  
Best Effort ◽  
Ltl Synthesis ◽  
Multiple Environments ◽  
Theoretic Characterization

We formally introduce and solve the synthesis problem for LTL goals in the case of multiple, even contradicting, assumptions about the environment. Our solution concept is based on ``best-effort strategies'' which are agent plans that, for each of the environment specifications individually, achieve the agent goal against a maximal set of environments satisfying that specification. By means of a novel automata theoretic characterization we demonstrate that this best-effort synthesis for multiple environments is 2ExpTime-complete, i.e., no harder than plain LTL synthesis. We study an important case in which the environment specifications are increasingly indeterminate, and show that as in the case of a single environment, best-effort strategies always exist for this setting. Moreover, we show that in this setting the set of solutions are exactly the strategies formed as follows: amongst the best-effort agent strategies for ɸ under the environment specification E1, find those that do a best-effort for ɸ under (the more indeterminate) environment specification E2, and amongst those find those that do a best-effort for ɸ under the environment specification E3, etc.

scholarly journals Best-Effort Synthesis: Doing Your Best Is Not Harder Than Giving Up

2021 ◽  
Author(s):  
Benjamin Aminof ◽  
Giuseppe De Giacomo ◽  
Sasha Rubin
Keyword(s):  
Computational Complexity ◽  
Optimal Algorithms ◽  
Best Effort ◽  
Ltl Synthesis

We study best-effort synthesis under environment assumptions specified in LTL, and show that this problem has exactly the same computational complexity of standard LTL synthesis: 2EXPTIME-complete. We provide optimal algorithms for computing best-effort strategies, both in the case of LTL over infinite traces and LTL over finite traces (i.e., LTLf). The latter are particularly well suited for implementation.

Dual systems for all: Higher-order, role-based relational reasoning as a uniquely derived feature of human cognition

2019 ◽  
Vol 42 ◽  
Author(s):  
Daniel J. Povinelli ◽  
Gabrielle C. Glorioso ◽  
Shannon L. Kuznar ◽  
Mateja Pavlic
Keyword(s):  
Temporal Reasoning ◽  
Higher Order ◽  
Important Case ◽  
Human Cognition ◽  
Relational Reasoning ◽  
Dual Systems ◽  
First Order ◽  
Reasoning System ◽  
Role Based

Abstract Hoerl and McCormack demonstrate that although animals possess a sophisticated temporal updating system, there is no evidence that they also possess a temporal reasoning system. This important case study is directly related to the broader claim that although animals are manifestly capable of first-order (perceptually-based) relational reasoning, they lack the capacity for higher-order, role-based relational reasoning. We argue this distinction applies to all domains of cognition.

The Multiple Environments in Which We Grow Old

1984 ◽  
Vol 29 (3) ◽  
pp. 230-231
Author(s):  
Frances M. Carp
Keyword(s):  
Multiple Environments

New Iterative Algorithms for Solving the Mixed Antenna Synthesis Problem

2002 ◽  
Vol 58 (9-10) ◽  
pp. 9
Author(s):  
Efim Grigor'evich Zelkin ◽  
Victor Filippovich Kravchenko ◽  
Miklhail Alekseevich Basarab
Keyword(s):  
Iterative Algorithms ◽  
Synthesis Problem ◽  
Antenna Synthesis

scholarly journals Ethnicity, Exclusion, and Exams: Education Policy and Politics in Burundi from the Independent Republics to the Civil War (1966–1993)

2021 ◽  
pp. 000203972110235
Author(s):  
Emily Dunlop
Keyword(s):  
Education Policy ◽  
Political Institutions ◽  
Important Case ◽  
Potential Mechanism ◽  
Social Hierarchies ◽  
Ethnic Inequalities ◽  
Policy Goals ◽  
Inequality In Education ◽  
Perceptions Of Inequality ◽  
Ethnicity And Politics

Education policy can embed ethnic inequalities in a country. Education in Burundi, with its historically exclusive political institutions and education, represents an important case for understanding these interactions. In this article, I interview twelve Burundians about how they experienced and perceived ethnicity and politics in their schooling from 1966 to 1993. I argue that education contributed to tangible and perceived social hierarchies based on ethnic inequalities. I show that this exclusion reflected both overt and covert policy goals, through proxies used to identify ethnicity in schools and through the exclusive nature of national exams at the time, which promoted members of the Tutsi minority at the expense of the majority Hutus. This study has implications for understanding how perceptions of inequality in education manifest as grievances against the state. It sheds light on the importance of understanding covert education policy as a potential mechanism for generating exclusion and contributing to conflict.

scholarly journals Conditional Entropy: A Potential Digital Marker for Stress

Entropy ◽  
2021 ◽  
Vol 23 (3) ◽  
pp. 286
Author(s):  
Soheil Keshmiri
Keyword(s):  
Resting State ◽  
Nearest Neighbor ◽  
Brain Activity ◽  
Solution Concept ◽  
Conditional Entropy ◽  
K Nearest Neighbor ◽  
Brain Response ◽  
Substantial Progress ◽  
Eeg Recordings ◽  
The Brain

Recent decades have witnessed a substantial progress in the utilization of brain activity for the identification of stress digital markers. In particular, the success of entropic measures for this purpose is very appealing, considering (1) their suitability for capturing both linear and non-linear characteristics of brain activity recordings and (2) their direct association with the brain signal variability. These findings rely on external stimuli to induce the brain stress response. On the other hand, research suggests that the use of different types of experimentally induced psychological and physical stressors could potentially yield differential impacts on the brain response to stress and therefore should be dissociated from more general patterns. The present study takes a step toward addressing this issue by introducing conditional entropy (CE) as a potential electroencephalography (EEG)-based resting-state digital marker of stress. For this purpose, we use the resting-state multi-channel EEG recordings of 20 individuals whose responses to stress-related questionnaires show significantly higher and lower level of stress. Through the application of representational similarity analysis (RSA) and K-nearest-neighbor (KNN) classification, we verify the potential that the use of CE can offer to the solution concept of finding an effective digital marker for stress.

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