Towards Artificial Intelligence: Concepts, Applications, and Innovations

Saba, Djamel; Sahli, Youcef; Maouedj, Rachid; Hadidi, Abdelkader; Medjahed, Miloud Ben

doi:10.1007/978-3-030-52067-0_6

Cited by 9 publications

(4 citation statements)

References 84 publications

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“…In the healthcare sector, AI approaches have been widely used due to the urgent challenges posed by the spread of viruses, particularly in the area of awareness and precaution [33]. Among the artificial intelligence approaches that have emerged with great effectiveness is an ontology that we have relied on to develop the solution.…”

Section: Analyze and Discussionmentioning

confidence: 99%

Development of an Ontology-Based Solution to Reduce the Spread of Viruses

et al. 2022

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With the sudden emergence of many dangerous viruses in recent years and with their rapid transmission and danger to individuals, most countries have adopted several strategies, such as closure and social distancing, to control the spread of the virus in the population. In parallel with all these precautions, scientific laboratories are working on developing the appropriate vaccine, which in many cases takes many years. Until then, it is necessary to resort to many solutions, including solutions that rely on information technologies and artificial intelligence (AI). In this context, this paper proposes a new solution based on the ontology and rules of intelligent reasoning. Initially, the virus environment is analyzed, followed by the extraction and editing of the main elements of the ontology using the “Protégé” software. In the last step, the proposed solution is tested, by choosing the city of Adrar in southwestern Algeria, which was particularly affected by COVID-19. Three scenarios were shown for different cases. The efficiency of the proposed solution was confirmed through the instructions it provides in the event of symptoms appearing in a person. In addition, this solution helps the competent authorities know the location and extent of the epidemic by informing the local communities.

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Section: Analyze and Discussionmentioning

confidence: 99%

Development of an Ontology-Based Solution to Reduce the Spread of Viruses

et al. 2022

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“…Zuboff's (2019) concept of the "surveillance capitalism" captures epoch were data commodification challenges traditional legal boundaries, signifying a broader transformation in law's response to a digitized society. Concurrently, rise of legal tech applications illustrates a shift towards data-driven legal decisions, embodying the heart of modern academic dialogue (Saba, Sahli, Maouedj, Hadidi & Medjahed, 2021).…”

Section: Literature Reviewmentioning

confidence: 99%

Pixels and Policy: The Symbiotic Relationship Between Digitalization and International Trade Legislation

Usman,

khaliq,

Shaheen

2023

JSRD

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In an era where digital frontier continually reshapes our jurisprudential landscape, this research embarks upon an odyssey to decipher its complex tapestry. Employing a qualitative approach, it delves deep into interplay between burgeoning data realms and legal scaffolds, drawing insights from extensive array of scholarly literature. The investigation unveils that confluence of data and law transcends mere operational shifts; it signals a profound transformation in our societal ethos. Findings underline the dual-edged nature of this evolution: while legal tech offers unparalleled chances for enhanced oversight and efficiency, it concurrently provokes challenges related to privacy & surveillance. In conclusion, as we stand at cusp of this digital jurisprudential metamorphosis, it becomes imperious to cultivate a balance, imbuing legal structures with prowess of technology yet anchored by enduring tenets of justice and human rights. The suggestions include fostering interdisciplinary dialogues & proactive regulatory frameworks, ensuring that our march into the digital future remains both the innovative and ethically grounded.

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“…There have been many attempts towards creating autonomous systems with the target of achieving human-level performance in different scenarios. These have led to the development of a number of novel state-of-the-art AI techniques in recent years (Vamvoudakis et al 2015;Saba et al 2021).…”

Section: Machine Autonomymentioning

confidence: 99%

An unsupervised autonomous learning framework for goal-directed behaviours in dynamic contexts

Ezenkwu

Starkey

2022

Adv. in Comp. Int.

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Due to their dependence on a task-specific reward function, reinforcement learning agents are ineffective at responding to a dynamic goal or environment. This paper seeks to overcome this limitation of traditional reinforcement learning through a task-agnostic, self-organising autonomous agent framework. The proposed algorithm is a hybrid of TMGWR for self-adaptive learning of sensorimotor maps and value iteration for goal-directed planning. TMGWR has been previously demonstrated to overcome the problems associated with competing sensorimotor techniques such SOM, GNG, and GWR; these problems include: difficulty in setting a suitable number of neurons for a task, inflexibility, the inability to cope with non-markovian environments, challenges with noise, and inappropriate representation of sensory observations and actions together. However, the binary sensorimotor-link implementation in the original TMGWR enables catastrophic forgetting when the agent experiences changes in the task and it is therefore not suitable for self-adaptive learning. A new sensorimotor-link update rule is presented in this paper to enable the adaptation of the sensorimotor map to new experiences. This paper has demonstrated that the TMGWR-based algorithm has better sample efficiency than model-free reinforcement learning and better self-adaptivity than both the model-free and the traditional model-based reinforcement learning algorithms. Moreover, the algorithm has been demonstrated to give the lowest overall computational cost when compared to traditional reinforcement learning algorithms.

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Towards Artificial Intelligence: Concepts, Applications, and Innovations

Cited by 9 publications

References 84 publications

Development of an Ontology-Based Solution to Reduce the Spread of Viruses

Development of an Ontology-Based Solution to Reduce the Spread of Viruses

Pixels and Policy: The Symbiotic Relationship Between Digitalization and International Trade Legislation

An unsupervised autonomous learning framework for goal-directed behaviours in dynamic contexts

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