<ul><li>In its most fundamental essence, the stuff of computing is symbol structures (systems of symbols, that is, entities that ‘stand for’, represent, or denote other entities like data, information or knowledge).</li><li>Computing is symbol processing. </li><li>Any automaton capable of processing symbol structures is a computer. </li><li>The ‘phenomena’ associated with computers as Perlis, Newell, and Simon suggested are all ultimately reducible to symbol structures and their processing. </li><li>We may choose to call such symbol structures information, data, or knowledge depending on the particular ‘culture’ within computer science to which we belong.</li><li>Computer science is, ultimately, the science of automatic symbol processing, an insight which Allen Newell and Herbert Simon have emphasized. </li></ul>

The Stuff of Computing

<ul><li>The modern computer is a hierarchically organized system of computational artefacts.</li><li>Hierarchical organization is a means of managing the complexity of an entity.</li><li>Computational artefacts are made things; they process symbol structures signifying information, data, or knowledge (depending on one’s point of view and context). </li><li>There are three classes of computational artefacts.</li><li>One class is material. These artefacts, like all material objects encountered through history, obey the physical laws of nature. e.g. all kinds of computer hardware.</li><li>Some computational artefacts, however, are entirely abstract. They not only process symbol structures, they themselves are symbol structures and are intrinsically devoid of any physicality. So physico-chemical laws do not apply to them. They neither occupy physical space nor do they consume physical time. e.g. algorithms, methodologies, languages, turing machines.</li><li>The third class of computational artefacts are the ones that most lend strangeness to computer science. These are abstract and material. To be more precise, they are themselves symbol structures, and in this sense they are abstract; yet their operations cause changes in the material world; moreover, their actions depend on an underlying material agent to execute the actions. Because of this nature, this class is called liminal (meaning a state of ambiguity, of between and betwixt). e.g. computer programs or software is one vast class of liminal computational artefacts.</li><li>Computer science is the science of computational artefacts.</li><li>Herbert Simon called all the sciences concerned with artefacts (abstract, liminal, or material) the sciences of the artificial. They stand apart from the natural sciences because they must take into account goals and purposes. A natural object has no purpose.</li><li>The sciences of the artificial entail the study of the relationship between means and ends: the goals or needs for which an artefact is intended, and the artefact made to satisfy the needs. The ‘science’ in computer science is, thus, a science of means and ends. It asks: given a human need, goal, or purpose, how can a computational artefact demonstrably achieve such a purpose? That is, how can one demonstrate, by reason or observation or experiment that the computational artefact satisfies that purpose?</li></ul>

Computational Artefacts

<ul><li>Algorithms are abstract artefacts.</li><li>They are procedural knowledge.</li><li>In order for a procedure to qualify as an algorithm as computer scientists understand this concept, it must possess the following attributes (as first enunciated by Donald Knuth):</li><li>Finiteness. An algorithm always terminates (that is, comes to a halt) after a finite number of steps.</li><li>Definiteness. Every step of an algorithm must be precisely and unambiguously specified.</li><li>Effectiveness. Each operation performed as part of an algorithm must be primitive enough for a human being to perform it exactly (using, say, pencil and paper).</li><li>Input and output. An algorithm must have one or more inputs and one or more outputs.</li><li>Donald Knuth (who perhaps more than any other person made algorithms part of the computer scientist’s consciousness) once described computer science as the study of algorithms. Not all computer scientists would agree with this ‘totalizing’ sentiment, but none could conceive of a computer science without algorithms at its epicentre. Much like the Darwinian theory of evolution in biology, all roads in computing seem to lead to algorithms. If to think biologically is to think evolutionarily, to think computationally is to form the habit of algorithmic thinking.</li></ul>

Algorithmic Thinking

<ul><li>Programs are liminal artefacts.</li><li>Programming languages, in contrast to natural ones, are invented or designed. They are, thus, artefacts. They entail the use of notation as symbols. As we will see, a programming language is actually a set of symbol structures and, being independent of physical computers, are abstract in exactly the same sense that algorithms are abstract. We thus have the curious situation that while programs written in such languages are liminal, the languages of programming themselves are abstract.</li></ul>

The Art, Science, and Engineering of Programming

<ul><li>The physical computer is the fundamental material computational artefact of interest to computer scientists.</li><li>The view of the physical computer as an abstract, symbol processing computational artefact constitutes the computer’s architecture.</li><li>A given architecture can be implemented using different technologies. Architectures are not independent of technologies in that developments in the latter influence architecture design, but there is a certain amount of autonomy or ‘degrees of freedom’ the designer of computer architectures enjoy. Conversely, the design of an architecture might shape the kind of technology deployed.</li><li>Computer architectures are thus liminal artefacts. The computer architect must navigate delicately between the Scylla of the computer’s functional and performance requirements and the Charybdis of technological feasibility.</li></ul>

The Discipline of Computer Architecture

<ul><li>Many problems are not conducive to algorithmic solutions.</li><li>Even if one understands the problem well enough, and possesses knowledge about the problem domain, and can construct an algorithm to solve the problem, the amount of computational resources (time or space) needed to execute the algorithm may be simply infeasible.</li><li>From an evolutionary point of view, algorithms are not all there is to our ways of thinking. And so the question arises: what other computational means are at our disposal to perform such tasks? The answer is to resort to a mode of computing that deploys heuristics.</li><li>Heuristics are rules, precepts, principles, hypotheses based on common sense, experience, judgement, analogies, informed guesses, etc., that offer promise but are not guaranteed to solve problems.</li><li>Heuristic computing embodies a spirit of adventure! </li><li>There is an element of uncertainty and the unknown in heuristic computing. </li><li>A problem solving agent (a human being or a computer) looking for a heuristic solution to a problem is, in effect, in a kind of terra incognita. And just as someone in an unknown physical territory goes into exploration or search mode so also the heuristic agent: he, she, or it searches for a solution to the problem, in what computer scientists call a problem space, never quite sure that a solution will obtain. </li><li>Thus one kind of heuristic computing is also called heuristic search.</li><li>Many strategies, however, that deploy heuristics have all the characteristics of an algorithm—with one notable difference: they give only ‘nearly right’ answers for a problem, or they may only give correct answers to some instances of the problem. </li><li>Computer scientists, thus, refer to some kinds of heuristic problem solving techniques as heuristic or approximate algorithms.</li><li>The term ‘heuristic computing’ encompasses both heuristic search and heuristic algorithms.</li></ul>

Heuristic Computing

<ul><li>Most sciences in the modern era—say, after the Second World War—are so technical, indeed esoteric, that their deeper comprehension remains largely limited to the specialists, the community of those sciences’ practitioners. Think, for example, of the modern physics of fundamental particles. At best, when relevant, their implications are revealed to the larger public by way of technological consequences.</li><li>Yet there are some sciences that touch the imagination of those outside the specialists by way of the compelling nature of their central ideas. The theory of evolution is one such instance from the realm of the natural sciences. Its tentacles of influence have extended into the reaches of sociology, psychology, economics, and even computer science, fields of thought having nothing to do with genes or natural selection.</li><li>Among the sciences of the artificial, computer science manifests a similar characteristic. I am not referring to the ubiquitous and ‘in your face’ technological tools which have colonized the social world. I am referring, rather, to the emergence of a certain mentality.</li><li>This mentality, or at least its promise, was articulated passionately and eloquently by one of the pioneers of artificial intelligence, Seymour Papert, in his book Mindstorms (1980).</li><li>Papert’s vision, rather, was the inculcation of a mentality that would guide, shape, and influence the ways in which a person would think about, perceive, and respond to, aspects of the world— one’s inner world and the world outside—which prima facie have no apparent connection to computing—perhaps by way of analogy, metaphor, and imagination.</li><li>Over a quarter of a century after Papert’s manifesto, computer scientist Jeanette Wing gave this mentality a name: computational thinking.</li><li>But Wing’s vision is perhaps more prosaic than was Papert’s. Computational thinking, she wrote in 2008, entails approaches to such activities as problem solving, designing, and making sense of intelligent behaviour that draws on fundamental concepts of computing. Yet computational thinking cannot be an island of its own. In the realm of problem solving it would be akin to mathematical thinking; in the domain of design it would share features with the engineering mentality; and in understanding intelligent systems (including, of course, the mind) it might find common ground with scientific thinking.</li><li>Like Papert, Wing disassociated the mentality of computational thinking from the physical computer itself: one can think computationally without the presence of a computer.</li></ul>

Computational Thinking

Over the past sixty years, the spectacular growth of the technologies associated with the computer is visible for all to see and experience. Yet, the science underpinning this technology is less visible and little understood outside the professional computer science community. As a scientific discipline, computer science stands alongside the likes of molecular biology and cognitive science as one of the most significant new sciences of the post Second World War era. In this Very Short Introduction, Subrata Dasgupta sheds light on these lesser known areas and considers the conceptual basis of computer science. Discussing algorithms, programming, and sequential and parallel processing, he considers emerging modern ideas such as biological computing and cognitive modelling, challenging the idea of computer science as a science of the artificial. ABOUT THE SERIES: The Very Short Introductions series from Oxford University Press contains hundreds of titles in almost every subject area. These pocket-sized books are the perfect way to get ahead in a new subject quickly. Our expert authors combine facts, analysis, perspective, new ideas, and enthusiasm to make interesting and challenging topics highly readable.

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Computer Science: A Very Short Introduction

<ul><li>The present is the past rolled up for action, and the past is the present unrolled for understanding.</li><li>We must operate with partial knowledge, and be provisionally content with probabilities.</li><li>Since man is a moment in astronomic time, a transient guest of the earth, a spore of his species, a scion of his race, a composite of body, character, and mind, a member of a family and a community, a believer or doubter of a faith, a unit in an economy, perhaps a citizen in a state or a soldier in an army, we may ask under the corresponding heads—astronomy, geology, geography, biology, ethnology, psychology, morality, religion, economics, politics, and war—what history has to say about the nature, conduct, and prospects of man.</li></ul>

Hesitations

<ul><li>Human history is a brief spot in space, and its first lesson is modesty.</li><li>History is subject to geology. </li><li>Climate no longer controls us but it limits us.</li><li>Geography is the matrix of history, its nourishing mother and disciplining home.</li><li>The influence of geographic factors diminishes as technology grows.</li><li>Only the imagination and initiative of leaders, and the hardy industry of followers, can transform the possibilities into fact.</li><li> Man, not the earth, makes civilization.</li></ul>

History & The Earth

<ul><li>History is a fragment of biology: the life of man is a portion of the vicissitudes of organisms on land and sea.</li><li>We are subject to the processes and trials of evolution, to the struggle for existence and the survival of the fittest to survive.</li><li>So the first biological lesson of history is that life is competition.</li><li>Co-operation is real, and increases with social development, but mostly because it is a tool and form of competition.</li><li>War is a nation’s way of eating. It promotes co-operation because it is the ultimate form of competition.</li><li>The second biological lesson of history is that life is selection.</li><li>Nature loves difference as the necessary material of selection and evolution.</li><li>Nature smiles at the union of freedom and equality in our utopias. For freedom and equality are sworn and everlasting enemies, and when one prevails the other dies.</li><li>The third biological lesson of history is that life must breed.</li><li>Nature has no use for organisms, variations, or groups that cannot reproduce abundantly.</li><li>She has a passion for quantity as prerequisite to the selection of quality.</li><li>Biologically, physical vitality may be, at birth, of greater value than intellectual pedigree.</li><li>So the birth rate, like war, may determine the fate of theologies.</li></ul>

Biology & History

<ul><li>Society is founded not on the ideals but on the nature of man, and the constitution of man rewrites the constitutions of states.</li><li>Human beings are normally equipped by “nature” with positive and negative instincts, whose function it is to preserve the individual, the family, the group, or the species.</li><li>Each instinct generates habits and is accompanied by feelings.</li><li>Their totality is the nature of man.</li><li>Evolution in man during recorded time has been social rather than biological.</li><li>Imitation is opposed to innovation, but in vital ways it co-operates with it.</li><li>As submissive natures unite with masterful individuals to make the order and operation of a society, so the imitative majority follows the innovating minority, and this follows the originative individual, in adapting new responses to the demands of environment or survival.</li><li>History in the large is the conflict of minorities; the majority applauds the victor and supplies the human material of social experiment.</li></ul>

Character & History

<ul><li>Nature and history do not agree with our conceptions of good and bad; they define good as that which survives, and bad as that which goes under.</li><li>Religion does not seem at first to have had any connection with morals. It was fear that first made the gods. Only when priests used these fears and rituals to support morality and law did religion become a force vital and rival to the state.</li><li>Religion has conferred meaning and dignity upon the lowliest existence.</li><li>Destroy that hope, and class war is intensified. Heaven and utopia are buckets in a well: when one goes down the other goes up. Puritanism and paganism—the repression and the expression of the senses and desires—alternate in mutual reaction in history.</li><li>Generally religion and puritanism prevail in periods when the laws are feeble and morals must bear the burden of maintaining social order.</li><li>There is no significant example in history, before our time, of a society successfully maintaining moral life without the aid of religion.</li><li>As long as there is poverty there will be gods.</li></ul>

Religion & History

<ul><li>All economic history is the slow heartbeat of the social organism, a vast systole and diastole of concentrating wealth and compulsive recirculation.</li></ul>

Economics & History

<ul><li>War is one of the constants of History and has not diminished with civilization or democracy. “Polemos pater panton” said Heracleitus; war, or competition, is the father of all things, the potent source of ideas, inventions, institutions, and states.</li><li>Peace is an unstable equilibrium, which can be preserved only by acknowledged supremacy or equal power.</li></ul>

History & War

<ul><li>Since men love freedom, and the freedom of individuals in society requires some regulation of conduct, the first condition of freedom is its limitation; make it absolute and it dies in chaos. So the prime task of government is to establish order; organized central force is the sole alternative to incalculable and disruptive force in private hands. Power naturally converges to a center, for it is ineffective when divided, diluted, and spread.</li><li>Monarchy seems to be the most natural kind of government. If we were to judge forms of government from their prevalence and duration in history we should have to give the palm to monarchy; democracies, by contrast, have been hectic interludes.</li><li>When it is hereditary it is likely to be more prolific of stupidity, nepotism, irresponsibility, and extravagance than of nobility or statesmanship</li><li>The complexity of contemporary states seems to break down any single mind that tries to master it.</li><li>Hence most governments have been oligarchies—ruled by a minority, chosen either by birth, as in aristocracies, or by a religious organization, as in theocracies, or by wealth, as in democracies.</li><li>If the majority of abilities is contained in a minority of men, minority government is as inevitable as the concentration of wealth; the majority can do no more than periodically throw out one minority and set up another.</li><li>In some cases outworn and inflexible institutions seem to require violent overthrow. But in most instances the effects achieved by the revolution would apparently have come without it through the gradual compulsion of economic developments</li><li>Since wealth is an order and procedure of production and exchange rather than an accumulation of (mostly perishable) goods, and is a trust (the “credit system”) in men and institutions rather than in the intrinsic value of paper money or checks, violent revolutions do not so much redistribute wealth as destroy it. There may be a redivision of the land, but the natural inequality of men soon re-creates an inequality of possessions and privileges, and raises to power a new minority with essentially the same instincts as in the old. The only real revolution is in the enlightenment of the mind and the improvement of character, the only real emancipation is individual, and the only real revolutionists are philosophers and saints.</li><li>Democracy is the most difficult of all forms of government, since it requires the widest spread of intelligence, and we forgot to make ourselves intelligent when we made ourselves sovereign. Education has spread, but intelligence is perpetually retarded by the fertility of the simple. A cynic remarked that “you mustn’t enthrone ignorance just because there is so much of it.” However, ignorance is not long enthroned, for it lends itself to manipulation by the forces that mold public opinion. It may be true, as Lincoln supposed, that “you can’t fool all the people all the time,” but you can fool enough of them to rule a large country.</li><li>Democracy is today sounder than ever before. It has defended itself with courage and energy against the assaults of foreign dictatorship, and has not yielded to dictatorship at home. But if war continues to absorb and dominate it, or if the itch to rule the world requires a large military establishment and appropriation, the freedoms of democracy may one by one succumb to the discipline of arms and strife. If race or class war divides us into hostile camps, changing political argument into blind hate, one side or the other may overturn the hustings with the rule of the sword. If our economy of freedom fails to distribute wealth as ably as it has created it, the road to dictatorship will be open to any man who can persuasively promise security to all; and a martial government, under whatever charming phrases, will engulf the democratic world.</li></ul>

Government & History

A concise survey of the culture and civilization of mankind, The Lessons of History is the result of a lifetime of research from Pulitzer Prize–winning historians Will and Ariel Durant. With their accessible compendium of philosophy and social progress, the Durants take us on a journey through history, exploring the possibilities and limitations of humanity over time. Juxtaposing the great lives, ideas, and accomplishments with cycles of war and conquest, the Durants reveal the towering themes of history and give meaning to our own.

Computer Science: A Very Short Introduction

The Lessons of History

Shailendra Singh