The study aimed to examine the Information Technology used and its effect on the nature of the work of the administrators at Al-Azhar University in Gaza. The researchers used the analytical descriptive method through a questionnaire randomly distributed among the employees of Al-Azhar University in Gaza. The study was conducted on a sample of 77 employees the response rate was 92.20%. The study reached a number of results, the most important of which is that there is a high degree of (...) Information Technology Used at Al-Azhar University- Gaza from the point of view of the administrative staff, where the percentage (74.14%). And that there is a high level of the prevailing the Nature of Administrators Work from the point of view of administrative staff, where the percentage (72.14%), there is a direct correlation between the Information Technology Used and the Nature of Administrators Work, there is a statistically significant effect of the Information Technology Used on the Nature of Administrators Work at the university, the absence of differences between the sample according to the variable (gender and variable age) in their perception of the Information Technology Used and the Nature of Administrators Work, there are differences of statistical Sig. in the perception depending on the variable of scientific qualification in Field of the Nature of Administrators Work, while there were no differences in Field: technology used, the differences in the Nature of Administrators Work according to the scientific qualification were in favor of those who obtained the diploma degree compared to postgraduate studies, the absence of differences in the perception of employees of the Information Technology Used and the Nature of Administrators Work according to the variable years of service, and the variable level of employment (manager, head of department, administrative officer), and the change of the workplace. The study reached a number of recommendations, the most important of which is the necessity of giving universities the opportunity to participate in decision-making, the continued administration of universities interest and continuous improvement of the performance of its employees, the need to strengthen the periodic evaluation of job performance and to inform the employees and to express their opinion, the importance of solving the problems of Employees and giving them the opportunity to contribute to solving their own problems, the need to use the method of rotation of employees and periodically, and the importance of strengthening the democratic leadership style and empowering university staff. (shrink)

The essay presents a novel counterexample to Causal Decision Theory (CDT). Its interest is that it generates a case in which CDT violates the very principles that motivated it in the first place. The essay argues that the objection applies to all extant formulations of CDT and that the only way out for that theory is a modification of it that entails incompatibilism. The essay invites the reader to find this consequence of CDT a reason to reject it.

The best justification of time-discounting is roughly that it is rational to care less about your more distant future because there is less of you around to have it. I argue that the standard version of this argument, which treats both psychological continuity and psychological connectedness as reasons to care about your future, can only rationalize an irrational—because exploitable—form of future discounting.

This discussion note examines a recent argument for the principle that any counterfactual with true components is itself true. That argument rests upon two widely accepted principles of counterfactual logic to which the paper presents counterexamples. The conclusion speculates briefly upon the wider lessons that philosophers should draw from these examples for the semantics of counterfactuals.

(No abstract is available for this citation).

The best-known argument for Evidential Decision Theory (EDT) is the ‘Why ain’cha rich?’ challenge to rival Causal Decision Theory (CDT). The basis for this challenge is that in Newcomb-like situations, acts that conform to EDT may be known in advance to have the better return than acts that conform to CDT. Frank Arntzenius has recently proposed an ingenious counter argument, based on an example in which, he claims, it is predictable in advance that acts that conform to EDT will do (...) less well than acts that conform to CDT. We raise two objections to Arntzenius’s example. We argue, first, that the example is subtly incoherent, in a way that undermines its effectiveness against EDT; and, second, that the example relies on calculating the average return over an inappropriate population of acts. (shrink)

The paper argues that on three out of eight possible hypotheses about the EPR experiment we can construct novel and realistic decision problems on which (a) Causal Decision Theory and Evidential Decision Theory conflict (b) Causal Decision Theory and the EPR statistics conflict. We infer that anyone who fully accepts any of these three hypotheses has strong reasons to reject Causal Decision Theory. Finally, we extend the original construction to show that anyone who gives any of the three hypotheses any (...) non-zero credence has strong reasons to reject Causal Decision Theory. However, we concede that no version of the Many Worlds Interpretation (Vaidman, in Zalta, E.N. (ed.), Stanford Encyclopaedia of Philosophy 2014) gives rise to the conflicts that we point out. (shrink)

Abstract. Suppose that the word of an eyewitness makes it 80% probable that A committed a crime, and that B is drawn from a population in which the incidence rate of that crime is 80%. Many philosophers and legal theorists have held that if this is our only evidence against those parties then (i) we may be justified in finding against A but not against B; but (ii) that doing so incurs a loss in the accuracy of our findings. This (...) paper argues against (ii). It argues that accuracy considerations can motivate taking different attitudes towards individualized and statistical evidence even across cases where they generate the same probability that the defendant is guilty. (shrink)

Background: Anemia is a condition that occurs due to a lower concentration of hemoglobin than the normal level (non-pregnant adult females less than 11 g / dL and males younger than 13 g / dL). Because of the low level of hemoglobin, the body's organs suffer from lack of enough oxygen, so patients complain of signs and symptoms such as fatigue, headaches, lack of concentration, lethargy and others. Objectives: The main goal of this expert system is to get the appropriate (...) diagnosis of disease. Methods: In this paper the design of the proposed Expert System which was produced to help Doctor in diagnosing many of the anemia diseases such as : Fatigue, Chest pain, Shortness of breath, Swelling of the body, Pallor of skin. The proposed expert system presents an overview about anemia diseases are given, the cause of diseases are outlined. SL5 Expert System language was used for designing and implementing the proposed expert system. Results: The proposed anemia diseases diagnosis expert system was evaluated by engineering students. (shrink)

A decision problem where Causal Decision Theory (CDT) declines a free $1,000, with the foreseeable effect that the agent is $1,000 poorer, and in no other way better off, than if she had taken the offer.

Knowledge-Based Systems (KBS) are computer programs based on technologies established by Artificial Intelligence research, which express some characteristics of human knowledge and expertise to perform tasks normally done by human experts. Thus, a knowledge-based system has two distinguishing features: a knowledge base and an inference engine. The first part, the knowledge base, represents facts about the world. The second part, the inference engine, allows new knowledge to be inferred. Most commonly, it can take the form of IF-THEN rules coupled with (...) forward or backward chaining approaches. The paper introduce the concept of knowledge based systems, Architecture of a Knowledge-Based System, Tools for Building Knowledge-Based System, and brief introduction to the most popular knowledge based systems found in the literatures. (shrink)

Andy Egan's Smoking Lesion and Psycho Button cases are supposed to be counterexamples to Causal Decision Theory. This paper argues that they are not: more precisely, it argues that if CDT makes the right call in Newcomb's problem then it makes the right call in Egan cases too.

Causal Decision Theory reckons the choice-worthiness of an option to be completely independent of its evidential bearing on its non-effects. But after one has made a choice this bearing is relevant to future decisions. Therefore it is possible to construct problems of sequential choice in which Causal Decision Theory makes a guaranteed loss. So Causal Decision Theory is wrong. The source of the problem is the idea that agents have a special perspective on their own contemplated actions, from which evidential (...) connections that observers can see are either irrelevant or invisible. (shrink)

The paper offers a model of Kant's claim that unity of consciousness entails objectivity of experience. This claim has nothing especially to do with thought, language or the categories but is a general truth about arbitrary signaling systems of the sort modeled in the paper. In conclusion I draw some consequences for various forms of idealism.

A choice function C is rational iff: if it allows a path through a sequence of decisions with a particular outcome, then that outcome is amongst the ones that C would have chosen from amongst all the possible outcomes of the sequence. This implies, and it is the strongest definition that implies, that anyone who is irrational could be talked out of their own preferences. It also implies weak but non-vacuous constraints on choices over ends. These do not include alpha (...) or beta. (shrink)

The main goals of Intelligent Tutoring Systems (ITS) are: providing highly developed instructional guidance on a one-to-one foundation that is improved than what is attained with traditional computer aided instruction and is analogous to that of a decent human tutor; and developing and testing models of intelligent processes associated with instruction. ITS is a subfield of artificial intelligence. ITS consists of four interacting components: the student model which embodies the student's present knowledge state, the pedagogical module which comprises appropriate instructional (...) measures which are depending on the content of the student model, the knowledge model which contains the domain knowledge, and the user interface model which permits an effective dialog among ITS and the user. Usually, the knowledge model is the central part in the instructional process but there is a diversity of approaches that also put the stress on the other components. In this paper we survey the existing intelligent tutoring system found in the literature prior to publishing it. There might be other intelligent tutoring systems that we have missed; but when found, they will be added to the next release of the intelligent tutoring systems survey. (shrink)

The main goals of Intelligent Tutoring Systems (ITS) are: providing highly developed instructional guidance on a one-to-one foundation that is improved than what is attained with traditional computer aided instruction and is analogous to that of a decent human tutor; and developing and testing models of intelligent processes associated with instruction. ITS is a subfield of artificial intelligence. ITS consists of four interacting components: the student model which embodies the student's present knowledge state, the pedagogical module which comprises appropriate instructional (...) measures which are depending on the content of the student model, the knowledge model which contains the domain knowledge, and the user interface model which permits an effective dialog among ITS and the user. Usually, the knowledge model is the central part in the instructional process but there is a diversity of approaches that also put the stress on the other components. In this paper we have surveyed 55 existing intelligent tutoring system found in the literature. There might be other intelligent tutoring systems that we did not include in the current survey; but when found, we will make sure to be included in the next release of the intelligent tutoring systems survey. (shrink)

The main goals of Intelligent Tutoring Systems (ITS) are: providing highly developed instructional guidance on a one-to-one foundation that is improved than what is attained with traditional computer aided instruction and is analogous to that of a decent human tutor; and developing and testing models of intelligent processes associated with instruction. ITS is a subfield of artificial intelligence. ITS consists of four interacting components: the student model which embodies the student's present knowledge state, the pedagogical module which comprises appropriate instructional (...) measures which are depending on the content of the student model, the knowledge model which contains the domain knowledge, and the user interface model which permits an effective dialog among ITS and the user. Usually, the knowledge model is the central part in the instructional process but there is a diversity of approaches that also put the stress on the other components. In this paper we have surveyed 68 existing intelligent tutoring system found in the literature. There might be other intelligent tutoring systems that we did not include in the current survey; but when found, we will make sure to be included in the next release of the intelligent tutoring systems survey. (shrink)

Rule-Based Systems (RBS) are computer programs based on technologies established by Artificial Intelligence research, which express some characteristics of human knowledge and expertise to perform tasks normally done by human experts. Thus, a Rule -based system has two distinguishing features: a Rule base and an inference engine. The first part, the Rule base, represents facts about the world. The second part, the inference engine, allows new knowledge to be inferred. Most commonly, it can take the form of IF-THEN rules coupled (...) with forward or backward chaining approaches. The paper introduce the concept of Rule based systems, Architecture of a Rule -Based System, Tools for Building Rule -Based System, and brief introduction to the most popular Rule based systems found in the literatures. (shrink)