Developing complex tasks to promote thinking and learning

2009 ◽  
pp. 109-138
Keyword(s):  
Complex Tasks

Enhancing Learning, Performance, and Adaptability for Complex Tasks

2005 ◽  
Author(s):  
Steve W. J. Kozlowski ◽  
◽  
Richard P. DeShon
Keyword(s):  
Learning Performance ◽  
Complex Tasks

scholarly journals The prototypes of nanozyme-based nanorobots

2020 ◽  
Vol 6 (6) ◽  
pp. 223-244
Author(s):  
Jiaying Xie ◽  
Yiliang Jin ◽  
Kelong Fan ◽  
Xiyun Yan
Keyword(s):  
Functional Nanomaterials ◽  
Promising Candidate ◽  
Future Directions ◽  
Complex Tasks ◽  
Logic Control ◽  
The Future ◽  
Flexible Designs

AbstractArtificial nanorobot is a type of robots designed for executing complex tasks at nanoscale. The nanorobot system is typically consisted of four systems, including logic control, driving, sensing and functioning. Considering the subtle structure and complex functionality of nanorobot, the manufacture of nanorobots requires designable, controllable and multi-functional nanomaterials. Here, we propose that nanozyme is a promising candidate for fabricating nanorobots due to its unique properties, including flexible designs, controllable enzyme-like activities, and nano-sized physicochemical characters. Nanozymes may participate in one system or even combine several systems of nanorobots. In this review, we summarize the advances on nanozyme-based systems for fabricating nanorobots, and prospect the future directions of nanozyme for constructing nanorobots. We hope that the unique properties of nanozymes will provide novel ideas for designing and fabricating nanorobotics.

scholarly journals Effect of Environmental Enrichment on the Brain and on Learning and Cognition by Animals

Animals ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 973
Author(s):  
Thomas R. Zentall
Keyword(s):  
Cognitive Abilities ◽  
Environmental Enrichment ◽  
Behavioral Effect ◽  
Enriched Environment ◽  
Main Concern ◽  
Accurate Assessment ◽  
Housing Conditions ◽  
Complex Tasks ◽  
Learning And Cognition ◽  
The Brain

The humane treatment of animals suggests that they should be housed in an environment that is rich in stimulation and allows for varied activities. However, even if one’s main concern is an accurate assessment of their learning and cognitive abilities, housing them in an enriched environment can have an important effect on the assessment of those abilities. Research has found that the development of the brain of animals is significantly affected by the environment in which they live. Not surprisingly, their ability to learn both simple and complex tasks is affected by even modest time spent in an enriched environment. In particular, animals that are housed in an enriched environment are less impulsive and make more optimal choices than animals housed in isolation. Even the way that they judge the passage of time is affected by their housing conditions. Some researchers have even suggested that exposing animals to an enriched environment can make them more “optimistic” in how they treat ambiguous stimuli. Whether that behavioral effect reflects the subtlety of differences in optimism/pessimism or something simpler, like differences in motivation, incentive, discriminability, or neophobia, it is clear that the conditions of housing can have an important effect on the learning and cognition of animals.

scholarly journals Endogenous Agency Problems and the Dynamics of Rents

2020 ◽  
Vol 87 (6) ◽  
pp. 2542-2567
Author(s):  
B Biais ◽  
A Landier
Keyword(s):  
Overlapping Generations ◽  
Agency Problems ◽  
Overlapping Generations Model ◽  
Complex Tasks ◽  
Complex Skills ◽  
Do So

Abstract While potentially more productive, more complex tasks generate larger agency rents. Agents therefore prefer to acquire complex skills, to earn large rents. In our overlapping generations model, their ability to do so is kept in check by competition with predecessors. Old agents, however, are imperfect substitutes for young ones, because the latter are easier to incentivize, thanks to longer horizons. This reduces competition between generations, enabling young managers to go for larger complexity than their predecessors. Consequently, equilibrium complexity and rents gradually increase beyond what is optimal for the principal and for society.

scholarly journals Fault Tolerant PLBGSA: Precedence Level Based Genetic Scheduling Algorithm for P2P Grid

2013 ◽  
Vol 2013 ◽  
pp. 1-13 ◽  
Author(s):  
Piyush Chauhan ◽  
Nitin
Keyword(s):  
Genetic Algorithm ◽  
Directed Acyclic Graph ◽  
Fault Tolerant ◽  
Scheduling Algorithm ◽  
Complex Task ◽  
Grid Scheduling ◽  
Complex Tasks ◽  
Small Organizations ◽  
Grid Resources ◽  
Desirable Trait

Due to monetary limitation, small organizations cannot afford high end supercomputers to solve highly complex tasks. P2P (peer to peer) grid computing is being used nowadays to break complex task into subtasks in order to solve them on different grid resources. Workflows are used to represent these complex tasks. Finishing such complex task in a P2P grid requires scheduling subtasks of workflow in an optimized manner. Several factors play their part in scheduling decisions. The genetic algorithm is very useful in scheduling DAG (directed acyclic graph) based task. Benefit of a genetic algorithm is that it takes into consideration multiple criteria while scheduling. In this paper, we have proposed a precedence level based genetic algorithm (PLBGSA), which yields schedules for workflows in a decentralized fashion. PLBGSA is compared with existing genetic algorithm based scheduling techniques. Fault tolerance is a desirable trait of a P2P grid scheduling algorithm due to the untrustworthy nature of grid resources. PLBGSA handles faults efficiently.

SUPPLY CHAIN FORMATION IN OPEN, MARKET-BASED MULTI-AGENT SYSTEMS

2002 ◽  
Vol 02 (03) ◽  
pp. 349-363 ◽  
Author(s):  
ANEURIN M. EASWARAN ◽  
JEREMY PITT
Keyword(s):  
Supply Chain ◽  
Service Providers ◽  
Search Algorithm ◽  
Multiple Criteria ◽  
Simultaneous Optimization ◽  
Open Market ◽  
Multi Agent Systems ◽  
Complex Tasks ◽  
Hierarchical Task Network ◽  
Service Allocation

Efficient allocation of services to form a supply chain to solve complex tasks is a crucial problem. Optimal service allocation based on a single criterion is NP-Complete. Furthermore, complex tasks in general have multiple criteria that may be conflicting and non-commensurable. This paper presents a two-stage brokering algorithm for optimal anytime service allocation based on multiple criteria. In the first stage, a hierarchical task network planner is used to identify the services required to solve a task. In the second stage, a genetic algorithm (GA) determines service providers based on multiple criteria to provide the services identified by the planner. We present our algorithm and results from various experiments conducted to analyze the effect of various parameters that influence the complexity of the problem. In general, the results show the GA finds optimal solutions much quicker than a standard search algorithm. The empirical results also indicate the performance of the algorithm is sub-linear or polynomial time for various parameters. The algorithm has the ability to deal with any number of criteria. By addressing this problem, we expand the range of problems being addressed to any that require simultaneous optimization of multiple criteria and/or planning.

Task Complexity and Affect in Collegiate Football

1989 ◽  
Vol 69 (2) ◽  
pp. 671-674 ◽  
Author(s):  
Robert W. McGowan ◽  
Barry B. Shultz
Keyword(s):  
Task Complexity ◽  
Complex Tasks ◽  
Collegiate Football

This research examined difference in affect of athletes performing complex tasks (offensive positions) and those performing relatively simple tasks (defensive positions). As hypothesized, defensive players were more vigorous than offensive players. Differences were also found between positions (linemen, backs, and quarterbacks). Results agreed with previous research on differences in affect between microcycles of training. Specifically, athletes about to perform relatively simple tasks appeared to utilize anger as a preevent motivating strategy. No differences in attentional styles were detected between offensive players and defensive players or among positions in collegiate football.

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