Towards Adaptive Enterprise

2020 ◽  
pp. 132-157
Author(s):  
Harshad Khadilkar ◽  
Aditya Avinash Paranjape
Keyword(s):  
Decision Making ◽  
Adaptive Control ◽  
Reinforcement Learning ◽  
State Of The Art ◽  
Business Environment ◽  
The State ◽  
Learning Needs

The key to a successful adaptive enterprise lies in techniques and algorithms that enable the enterprise to learn about its environment and use the learning to make decisions that maximize its objectives. The volatile nature of the contemporary business environment means that learning needs to be continuous and reliable, and the decision-making rapid and accurate. In this chapter, the authors investigate two promising families of tools that can be used to design such algorithms: adaptive control and reinforcement learning. Both methodologies have evolved over the years into mathematically rigorous and practically reliable solutions. They review the foundations, the state-of-the-art, and the limitations of these methodologies. They discuss possible ways to bring together these techniques in a way that brings out the best of their capabilities.

The Sustainable Project Management Model

2018 ◽  
Author(s):  
Mohamed Salama ◽  
Jelena Janjusevic
Keyword(s):  
Project Management ◽  
State Of The Art ◽  
Sharing Economy ◽  
Business Environment ◽  
Digital Transformation ◽  
The State ◽  
Management Model ◽  
Disruptive Technologies ◽  
Economy Change ◽  
Rough Sea

In the era of digital transformation, following the emergence of disruptive technologies that guided and facilitated the shift towards sharing economy, change is imperative. Imagine the very nice-looking carriages that you see in the royal weddings and compare them to the latest generation of Tesla cars. Or compare the set of skills required to fly Yakovlev Air-5 model 1931 vis-a-vis the Dassault Rafale or the F16 Fighting Falcon (Top 10 fighters, 2017). Before embarking on driving/flying the latter, regardless how competent with the former, the driver/pilot needs to acquire relevant knowledge and master a new set of skills and techniques, and learn different methods in order to be able to deal with the state-of-the-art technology. The vibrant business environment that has become even turbulent amid the digital transformation is analogous to the rough sea with unfavourable conditions. Those who are not ahead of the game, vigilant, and aware of what they need to do in order to sail safe will have an unpleasant ending, regardless of how successful they are at present. The Titanic is just one example.

scholarly journals Dialogue Generation: From Imitation Learning to Inverse Reinforcement Learning

2019 ◽  
Vol 33 ◽  
pp. 6722-6729 ◽  
Author(s):  
Ziming Li ◽  
Julia Kiseleva ◽  
Maarten De Rijke
Keyword(s):  
Reinforcement Learning ◽  
State Of The Art ◽  
The State ◽  
Experimental Results ◽  
Imitation Learning ◽  
Local Optimum ◽  
Inverse Reinforcement Learning ◽  
High Quality ◽  
Overall Performance

The performance of adversarial dialogue generation models relies on the quality of the reward signal produced by the discriminator. The reward signal from a poor discriminator can be very sparse and unstable, which may lead the generator to fall into a local optimum or to produce nonsense replies. To alleviate the first problem, we first extend a recently proposed adversarial dialogue generation method to an adversarial imitation learning solution. Then, in the framework of adversarial inverse reinforcement learning, we propose a new reward model for dialogue generation that can provide a more accurate and precise reward signal for generator training. We evaluate the performance of the resulting model with automatic metrics and human evaluations in two annotation settings. Our experimental results demonstrate that our model can generate more high-quality responses and achieve higher overall performance than the state-of-the-art.

scholarly journals Spam Review Detection:A Systematic Literature Review

2020 ◽  
Author(s):  
Muhammad Shoaib Farooq
Keyword(s):  
Machine Learning ◽  
Decision Making ◽  
Literature Review ◽  
Systematic Literature Review ◽  
State Of The Art ◽  
The State ◽  
Research Gaps ◽  
Art Research ◽  
Fake Reviews ◽  
Research Studies

In this era of technology, people rely on online posted reviews before buying any product. These reviews are very important for both the consumers and people. Consumers and people use this information for decision making while buying products or investing money in any product. This has inclined the spammers to generate spam or fake reviews so that they can recommend their products and beat the competitors. Spammers have developed many systems to generate the bulk of spam reviews within hours. Many techniques, strategies have been designed and recommended to resolve the issue of spam reviews. In this paper, a complete review of existing techniques and strategies for detecting spam review is discussed. Apart from reviewing the state-of-the-art research studies on spam review detection, a taxonomy on techniques of machine learning for spam review detection has been proposed. Moreover, its focus on research gaps and future recommendations for spam review identification.

scholarly journals Rise of multiattribute decision‐making in combating COVID‐19: A systematic review of the state‐of‐the‐art literature

2021 ◽  
Author(s):  
Mohammed Assim Alsalem ◽  
Rawia Mohammed ◽  
Osamah Shihab Albahri ◽  
Aws Alaa Zaidan ◽  
Abdullah Hussein Alamoodi ◽  
...  
Keyword(s):  
Systematic Review ◽  
Decision Making ◽  
State Of The Art ◽  
The State

scholarly journals Read, Watch, and Move: Reinforcement Learning for Temporally Grounding Natural Language Descriptions in Videos

2019 ◽  
Vol 33 ◽  
pp. 8393-8400 ◽  
Author(s):  
Dongliang He ◽  
Xiang Zhao ◽  
Jizhou Huang ◽  
Fu Li ◽  
Xiao Liu ◽  
...  
Keyword(s):  
Decision Making ◽  
Reinforcement Learning ◽  
Natural Language ◽  
State Of The Art ◽  
Sliding Window ◽  
Sequential Decision Making ◽  
Sequential Decision ◽  
Boundary Information ◽  
Performance Gains ◽  
Steady Performance

The task of video grounding, which temporally localizes a natural language description in a video, plays an important role in understanding videos. Existing studies have adopted strategies of sliding window over the entire video or exhaustively ranking all possible clip-sentence pairs in a presegmented video, which inevitably suffer from exhaustively enumerated candidates. To alleviate this problem, we formulate this task as a problem of sequential decision making by learning an agent which regulates the temporal grounding boundaries progressively based on its policy. Specifically, we propose a reinforcement learning based framework improved by multi-task learning and it shows steady performance gains by considering additional supervised boundary information during training. Our proposed framework achieves state-of-the-art performance on ActivityNet’18 DenseCaption dataset (Krishna et al. 2017) and Charades-STA dataset (Sigurdsson et al. 2016; Gao et al. 2017) while observing only 10 or less clips per video.

Continuous Assurance and the Use of Technology for Business Compliance

2018 ◽  
pp. 820-830 ◽  
Author(s):  
Rui Pedro Figueiredo Marques
Keyword(s):  
Decision Making ◽  
Information Systems ◽  
Organizational Context ◽  
State Of The Art ◽  
The State ◽  
Reliable Information ◽  
Comprehensive Understanding ◽  
Use Of Technology ◽  
Assurance Services

In the current organizational context, in which there is a fierce competitiveness and a constant need for more timely, relevant and reliable information to support the decision making and achieve the strategic and operational objectives, Continuous Assurance has assumed an important role as a management goal and in ensuring improved effectiveness of organizations. This works provides the concept of Continuous Assurance, its objectives and components, and a model which allows both to evaluate information systems with Continuous Assurance services and to help design the requirements of new ones. Finally, some implementations are also presented providing a comprehensive understanding the state-of-the-art and the benefits of Continuous Assurance.

Continuous Assurance and the Use of Technology for Business Compliance

2019 ◽  
pp. 429-441 ◽  
Author(s):  
Rui Pedro Figueiredo Marques
Keyword(s):  
Decision Making ◽  
Information Systems ◽  
Organizational Context ◽  
State Of The Art ◽  
The State ◽  
Reliable Information ◽  
Comprehensive Understanding ◽  
Use Of Technology ◽  
Assurance Services

In the current organizational context, in which there is a fierce competitiveness and a constant need for more timely, relevant, and reliable information to support the decision making and achieve the strategic and operational objectives, continuous assurance has assumed an important role as a management goal and in ensuring improved effectiveness of organizations. This chapter provides the concept of continuous assurance, its objectives and components, and a model that allows both to evaluate information systems with continuous assurance services and to help design the requirements of new ones. Finally, some implementations are also presented providing a comprehensive understanding of the state of the art and the benefits of continuous assurance.

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