Defence`s Feeds

(Editor’s note: Adam Elkus is a PhD student at George Mason University working on computation and strategy)

Recently, KCL’s Kenneth Payne published an article on the potential meaning of artificial intelligence for future strategy. Some of the complexities of tackling this science fiction-esque topic lie in the duality of AI itself as a scientific discipline. While many believe that AI is a discipline oriented around the engineering of synthetic intelligence, one should also note that it has also alternatively claimed that doing so will help us understand human (and other forms of) intelligence. For example, Herbert Simon and Alan Newell’s General Problem Solver was an endeavor with relevance for both AI and cognitive science. Simon and Newell derived the idea of means-end reasoning from a view of human problem solving and implemented it programmatically in a way that could be mechanized by a machine. The same holds true for artificial neural networks as well, which are based somewhat on ideas from computational neuroscience and much more so on engineering utility for problems in machine learning.

Payne and his co-author Kareem Ayoub focus in particular on the use of games and microworlds to develop AI systems:

More complex scenarios than Atari games are possible. Microworlds are abstract representations used by the military to assist in strategic decision-making. They have been used to conceptualise the terrain, force deployment, enemy responses and movements. The use of modular AI in this example domain allows users to create their own microworld simulation with its own rules of play and run limitless iterations of possible events. Jason Scholz and his colleagues found that a reinforcement-learning based AI outperformed human counterparts in these microworld wargames. Their ability to do this rested on two factors: (1) the machine could go through rounds much faster than a human counterpart, and (2) the machine could process every possible move simultaneously, providing previously unseen recommendations.  Allowing that many military campaigns can be dimensionally reduced to microworlds – indeed many tabletop staff college exercises do precisely that – such an approach with modular AI proves valuable for rapid iteration of potential options.

A worthy addition to this observation, however, is that microworlds such as strategy games presume a certain view of human problem-solving behavior that is relatively new to strategic theory. [0] Consider the machine representation of chess, the most famous strategic game played by humans and computers. Like game theory, chess is can be visualized via extended-form representation, as seen in images like this:

The minimax algorithm visualizes strategy in terms of how both “min” and “max” players connect the initial moves to the payoff values in the terminal nodes at the bottom of the tree. The goal of min is to force the max player to the lowest payoff. Conversely, max would like to receive the highest payoff value. For a full explanation of minimax, readers are advised to consult the nearest friendly neighborhood game theorist, such as political scientist Phil Arena.  [1] Yet despite the fact that zero-sum games in game theory and chess share the same basic representation and solution concept, they diverge in one peculiar way.

The following image does not build the full game tree; notice that it only partially encompasses it:

This is due to the problem of how chess is represented on a machine; building the full game tree would be intractable due to the sheer size of the game. Moreover, a chess program would not be able to reason about other games that lack chess’ peculiar characteristics. [2] Two methods that have been commonly used to explain how humans and machines deal with chess’ sheer complexity are knowledge representation and search:

Given the relatively slow rate at which moderately skilled players can generate analysis moves, estimated in Charness (1981b) to be about four moves per minute, it is obvious that much of the time that human players spend is not in generating all possible moves (perhaps taking a move per second) but in generating moves selectively and using complex evaluation functions to assess their value. Computer chess programs can achieve high-level play by searching many moves using fast, frugal evaluation processes that involve minimal chess knowledge to evaluate the terminal positions in search. Deep Blue, the chess program that defeated World Champion Garry Kasparov in a short match in 1997, searched hundreds of millions of positions per second. Today’s leading microcomputer chess programs, which have drawn matches with the best human players, have sophisticated search algorithms and attempt to use more chess knowledge but still generate hundreds of thousands or millions of chess moves per second. Generally,   chess programs rely on search more heavily than knowledge; for humans it is the reverse. Yet, each can achieve very high performance levels because knowledge and search can trade off (Berliner & Ebeling, 1989).

Both knowledge and search, however, stem from the same fundamental way that old-school cognitive scientists and computer scientists define the problem of strategy, which is very different how the strategic studies profession views it. First, let us note therepresentation of game states as a hierarchal tree that proceeds from most abstract to most primitive; it takes us the entire time to move from the top of the tree to the end of the game and the actual payoffs. Another example can be found in the way in which hierarchal task network planning algorithm in AI begins with composite tasks and breaks them down until the algorithm reaches simple actions, which vaguely corresponds to distinctions of strategy and tactics known to Kings of War readers:

Computer-literate readers will also notice the similarity to this tree structure and the directory structure on a computer filesystem. [3]

Why does it make sense to view the world as a tree that moves from most general to most specific? This is an interesting topic about which a good deal of intellectual history was been written. Broadly speaking, it is not surprising that Cold War-era efforts to optimize hierarchally organized systems such as military bureaucracies produced a view of the world as a hierarchally decomposed tree. But that in and of itself does not fully explain the choice of representation. Ontologies, taxonomies, and other forms of hierarchal knowledge representation are common in science and philosophy. What computing did was make them dynamic processes. The interaction or composition of components produced behavior.

George Miller, the famous cognitive scientist, produced a book titled Plans and the Structure of Behavior. In contrast to behaviorist conceptions that did not envision much of an intermediary structure between stimulus and behavior, Miller and his counterparts in AI argued that the internal organization of cognition could tell us much about the outward manifestations of complex behaviors. Hence, it makes sense to study chess players in terms of how they organize their knowledge and search processes, as such internal representation could tell us much about how they are capable of producing complex strategies.

While deep neural networks are often viewed as oppositional to this broadly cognitivist view, this is not necessarily the case. [4] After all, one sees hierarchal representations (albeit defined highly differently) frequently in deep learning research. Hierarchal representations are key to recent research in reinforcement learning as well. And hierarchies also appear quite frequently in both AI work on evolving neural networks and neuroscience research on computation in the brain. Finally, one should also note that hierarchy (differing levels of abstraction) and modularity (different functions) appear to be one of the more interesting explanations for what ideas about animal behavior have in common with computing.

The consequences of this view are that the principal problems of strategy, seen computationally, lie in computational limitations.

The main problem for action selection is combinatorial complexity. Since all computation takes both time and space (in memory), agents cannot possibly consider every option available to them at every instant in time. Consequently, they must be biased, and constrain their search in some way. For AI, the question of action selection is: what is the best way to constrain this search? For biology and ethology, the question is: how do various types of animals constrain their search? Do all animals use the same approaches? Why do they use the ones they do?  …. Ideally, action selection itself should also be able to learn and adapt, but there are many problems of combinatorial complexity and computational tractability that may require restricting the search space for learning.

The core problem with a computational view of strategic behavior is that it views strategy in terms of the interface between an “outer environment” and an “inner environment.” If the inner environment of an artifact is well adapted to the outer environment that surrounds it, it will serve its purpose. In other words, if, say, the Department of Defense is able to configure its force structure and military operational concepts to meet the threat of X or Y adversary, its “inner environment” is well-adapted to realize the intended purpose of war and defense. This sort of view of strategy and defense underlies both systems analysis and net assessment, though net assessment is far more qualitative and eclectic. It also underlies the idea of ends, ways, and means held by many strategists – we must find the correct configuration of ways (actions) and means (resources) to meet the desired end. [5]

Let us contrast this to a more classical view of strategy, which would see strategy as the way in which a political community finds a way of fulfilling a desired purpose through the instrumental usage of violence. Here, the problem is not really the combinatorial complexity of searching for a path to the goal or optimizing a utility function, but in the difficult process of using social action to achieve a desired end. First, the end might be contested or ambiguously defined. As KCL PhD candidate Nick Prime and I noted, many strategic ends are essentially compromises and products of fractious politics. Second, what it means to fulfill it is always fairly uncertain during the actual process of strategy formulation.

Mathematically measured criteria are useful for measuring the distance between intention and goal, but metrics of progress depend on highly subjective definitions of not only the goal but also what it means to realize it. Defining the problem in Vietnam, for example, in terms of eradicating enemy infrastructure in South Vietnam presumes that the most important problem lies in Vietcong “shadow governments” that erode power and authority. This is a highly contestable view of the problem, because a combination of targeted killings and the toll of the failed Tet Offensive wiped out enemy infrastructure inside South Vietnam and we still failed to achieve our strategic goals.

Computation is likely a very useful model for thinking about strategy, especially (as Ayoub and Payne do) from a machine’s point of view. But it should also be observed just how alien this view is from the perspective of classical strategy, and recognized that no model is the territory. As a computer modeler, I never assume that any abstractions I build for coursework are anything but reductions of the “real” thing. [6] As computers become more and more present in strategy and command, we should keep these thoughts and the distinctions they suggest in mind. But is there any middle ground?

One meeting ground between the “system” view of strategy and the more humanistic view can be found potentially in the idea of “control” expressed by J.C. Wylie and others.

Control denotes the utility of strategy being found in the way in which an agent is able to manipulate the key features of the environment in a way that advantages the strategist and disadvantages the opponent. The classical view of computation and behavior in AI and cognitive science has been opposed by another set of views that de-emphasizes elaborate internal representation and emphasizes the way in which interaction with the environment produces intelligent behavior. [7]

The environment defines a relation between environmental object and an organism that affords the organism with the capability to perform a certain action. Control of the sea, for example, affords certain strategic capabilities that airpower and landpower does not, and vice versa. The simplest way of designing a mobile robot around its environment, for example, would start with basic behaviors (if X stimulus, perform Y action) and then utilize more complex control structures to inhibit or favor certain behaviors based on the situation. One behavior might be privileged over another even if they both correspond to the same environmental input. Hence, by changing the nature and pattern of the environment to your advantage, you in term exert control over your opponent. If I am playing hide-and-seek with a TurtleBot, for example, I can thwart my Dalek-like adversary if I re-arrange the topology of my apartment as to frustrate it in numerous ways. [8]

Food for thought, certainly. Meanwhile I will continue to dump Golang code into my ParrotAR in the vain hope that I can engineer a taco copter to deliver me tacos while I do research. I at least know that robots can deliver coffee, which is a good start. I can live without tacos but its hard to see how a PhD student can be “intelligent” without any coffee.

 

Adam Elkus is a PhD student in Computational Social Science at George Mason University and a 2015-2016 New America Foundation fellow in NAF’s Cybersecurity Initiative. He writes on strategy, technology, and other subjects while finding time to ponder how a drone can deliver tacos to his domicile.

[0] It is rather old in the social and behavioral sciences as well as other fields. See Margaret Boden’s Mind as Machine for a good history of the cognitive science view. Lawrence Freedman and Nils Gilman have aptly covered the social science literature.

[1] You can use Manhattan distance or some other metric to compute what is “near” in this statement.

[2] Chess and machines have a very old and interesting history. For more, see this handy overview of computer chess.

[3] This is a representation of the UNIX filesystem structure. See this article for an overview of the distinction between Linux and Windows filesystems. Linux and Mac OSX also differ in their interpretations of the basic UNIX structure. For more, see this and this.

[4] Connectionism (known as the Parallel Distributed Processing research program) in artificial intelligence and cognitive science is a different level of analysis. To see how the classical conception of AI and cogsci perceives mind, consult the physical symbol systems hypothesis.

[5] Indeed, Ends-Ways-Means can be viewed as a kind of organizational programming, as implied by Antulio Echevarria here and stated more bluntly by Christopher Paparone here.

[6] For a dense look at the philosophy of simulation, I recommend Manuel De Landa’s book on “synthetic reason.”

[7] It’s worth noting that the answer to understanding rationality probably lies in a combination of both. See this recent overview of new work in neuroscience and AI.

[8] There are two design strategies in AI, broadly. Make a simple organism that can be effective in a range of environments or build a highly brittle and complicated system for a well-defined environment. See Poole and Mackworth for more.

The Royal Australian Navy (RAN) has commissioned HMAS Adelaide, the second of two landing helicopter docks (LHDs), in Garden Island, Sydney.

The US Navy has accepted Lockheed Martin's fourth Mobile User Objective System (MUOS) satellite after the recent completion of on-orbit testing.

The US and Malaysian navies have agreed to review and establish plans for joint training and exercises in 2016 and beyond.

The Indian Navy has decided to dispose of the defunct submarine INS Sindhurakshak, following a feasibility study about its reuse.

Chinese AFT-9 Anti-Tank Missile Carrier

RAF Tornados, supported by Voyager tanker and a Reaper UAV, have extended the UK’s airstrikes to Syria. Hours after the UK parliament approved to extend the airstrikes to include Syria, Royal Air Force Tornado attack planes, deployed to Akrotiri, Cyprus, flew their first raid on terrorist targets inside Syria, early in the morning on Dec. […]

Sener technology and engineering group, a world reference in the marine field, organised its first Foran Day in Singapore with a great welcome of actors of shipbuilding industry in the region.

Navantia has the pleasure in delivering the final batch of four LLCs to the Commonwealth in Sydney.

Watch these U-2 Dragon Ladies land at RAF Fairford. Taken on Jun. 9, 2015 this interesting footage shows why the Dragon Lady is one of the most difficult plane to land in the world. As we have already seen in the U-2 clips taken at Beale Air Force Base, this iconic reconnaissance aircraft requires some special […]

The BaToLUS project, Battle Damage Tolerance for Lightweight Unmanned Aerial Vehicle (UAV) Structures, brought about a successful development of new rapid prototype modelling capabilities.

The BaToLUS project involved major European aeronautical industries, top-rated European research institutes and also small European enterprises. The European Defence Agency (EDA) led cooperation brought together a "critical mass" for an effective scientific dialogue, thus allowing the Nations to benefit from synergies in their respective industrial capabilities.

Compared to more conventional combat aircraft designs, extremely lightweight structures exhibit different distributions of strength and stiffness. Within the BaToLUS project, cost-efficient alternatives to a well-defined baseline configuration have been developed by improved structural design, aiming to offer increased tolerance against battle damage, whilst supporting the original requirements and keeping potential penalties small. 

Thanks to BaToLUS, new rapid prototype modelling capabilities have been developed. Also, a generic design process, which includes “Vulnerability Load Cases", and novel high-fidelity simulation methods have been demonstrated. A large number of structural concepts for vulnerability reductions have been identified, assessed and – for two of them – implemented and tested. Operational evaluation with respect to impacts on cost, weight and capabilities were considered at an overall platform level, together with vulnerability analysis taking into account the demonstrated structural performance and aerodynamic damage characterisation.

The main objectives of the project have been: (i) defining a UAV design and development process for vulnerability reduction to be integrated in the design process, (ii) demonstrating an improvement of the current UAV modelling, simulation and design capabilities, and (iii) providing a guideline on the costs associated with the development of a vulnerability-improved UAV.

The BaToLUS project was managed and funded by Germany, France, Sweden, and the UK in the frame of the European Defence Agency, and carried out by Airbus Defence & Space Germany (project leader), Airbus Group Innovations France, BAE Systems, CEA Gramat, Dynamec Research AB, Fraunhofer-Institut für Kurzzeitdynamik - Ernst-Mach-Institut (EMI), Industrieanlagen-Betriebsgesellschaft mbH (IABG), ONERA – The French Aerospace Lab, and SAAB Aerosystems.

More information:

• More details about the BaToLUS project
• About Capability Technology Areas 

 

A great fuss is being made over the speech by Labour shadow foreign secretary Hillary Benn in yesterday’s House of Commons debate over bombing in Syria. Watch for yourself, if you like, or I’ll paraphrase:

Islamic State is bad, super bad, Mussolini bad.

We should do something. Not something adequate. But something.

If we don’t then we’ll look stupid and weak and our friends will be sad.

Now face the firepower of this fully armed and operational battle station…err, well maybe a dozen or so 30 year old RAF Tornados!

I can’t fathom the acclaim for it.

First, attacking Islamic state in Syria does nothing to prevent attacks here in Europe. This argument has been so comprehensively debunked that I can hardly believe anyone still tries it on.

Second, yes, sure we are at war with a mood in the Islamic world of sullen resentment that we might as well call Islamic fascism, though really I’m not sure that Benn really grasped that this was the phrase he was resurrecting. Next up: it’s a crusade? But you can’t go name check Hitler and Mussolini and wax lyrical about this island’s brave stand against tyranny and then pretend that a few more British  bombers in the Middle East is any sort of proportionate response. People may be somnolent and distracted but they’re not so stupid as to miss the giant gap between rhetoric and action.

Third, going to war against an enemy in this desultory fashion that by design can never lead to victory just puts them under a natural selection pressure that insures that they evolve into something more nasty and resilient. Have we literally learned nothing from the last 15 years? How many times does it have to be said that you can’t fight wars amongst the people without being actually amongst them?

Fourth, why does it not seem to worry everyone who voted for bombing that the countries of the region that have more than enough power to deal with Islamic state actually don’t seem to care all that much about it? They’re more concerned with Houthi militiamen allegedly propped up by Persian bogeymen.

So, let’s take stock of the situation. We have no plausible aim. Therefore there is no meaningful strategy. In any event the means available are inadequate. We have very little knowledge of those whom we’ll be killing. And we have very little knowledge of those upon whose supposed behalf we’ll be doing it. The commitment of our friends to the effort is as guarded and ambiguous as our own while the commitment of our enemies is seemingly quite total. Meanwhile, every country in the region is playing a double or triple game. Basically everybody is lying to everyone else but the biggest dummies are lying to themselves.

I’m sure it will all work out great.

I do suppose though it makes bad war it’s probably good political theatre in a junior school sort of way. Jeremy Corbyn’s forced to sit on a tack. Haha! And when it comes Britain’s turn to suffer a Beslan-Mumbai-Nairobi-Utoya-Paris style attack, as it inevitably will, Westminster will claim it did all it could.

*actually, I don’t know. We’ve had a lot of wars, many quite stupid but this one really ranks up there.

btw, buy my book. It explains everything.

This week, Chief Executive Jorge Domecq updated the European Parliament’s security and defence subcommittee on the outcome of the recent EDA Ministerial Steering Board, the current security situation, the future of the European Defence Agency (EDA) and the Global Strategy.

Against the background of the atrocious terrorist attacks in Paris, Mr. Domecq emphasised the need to further develop European defence integration, “We need the right capabilities, a sound European armament policy supporting our defence industries, enhanced civil-military synergies and EU-NATO relations to make a quantum leap.”

In his update, Mr. Domecq stressed that the upcoming Global Strategy as well as the European Commission’s European Defence Action Plan were opportunities to address crucial elements for defence cooperation, the development of capabilities as well as strengthening of the European Defence and Industry Technological Base to safeguard Europe’s strategic autonomy.

Mr. Domecq also briefed Members of Parliament on the progress of the four capability programmes (air-to-air refuelling, cyber defence, Remotely Piloted Aircraft Systems and governmental satellite communications) as well as on future cooperative programmes recently approved by Ministers of Defence (deployable bio-laboratory, Medevac and anti-tank weapons).

Other initiatives in which the Agency has made progress in recent months include incentives for defence cooperation and mainly the VAT exemption for EDA projects, barter mechanisms, hybrid warfare. The Agency continues to working closely with the European Commission on the Preparatory Action on defence-related research as well as on facilitating access to EU instruments and funds for European companies working on dual-use technologies. Chief Executive Domecq also gave an update on the Agency’s work on wider EU policies and mainly on SES/SESAR, REACH and Energy.

He concluded his intervention by discussing the future role and direction of the Agency. The EDA is at the service of Member States and he insisted that there are five areas where Member States could and should make greater use of the Agency: 1) to use the Capability Development Plan as a real tool for defence planning, 2) systematic use of enablers, 3) the Preparatory Action on CSDP-related research should be the catalyst for greater engagement in cooperative defence R&T, 4) systematic harnessing of civil-military synergies, 5) using the EDA to make better use of available EU funding.

 

More information:

• Mr. Domecq's intervention is available here.
• European Parliament defence and security subcommittee

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(U.S. Navy photo by HMC Josh Ives/released) Last week, Britain’s prime minister David

We are currently conducting some research exploring the topic of interoperable open architecture within the military and how this approach may affect standards and requirements in the future. If you are working in this field or have knowledge of the technology and its applications we a

Following the downing of the Su-24 Fencer on Nov. 24, Russian attack planes fly with air-to-air missiles for self-protection. The Russian Air Force has decided to arm the Su-34 Fullback attack planes based at Latakia, in Syria, with air-to-air missiles to enhance the defensive capabilities of the aircraft conducting air strikes against terrorists across the […]

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In this interview, Daniel Fiott talks with Olivier de France about how various elements of French society are reacting to the 13 November Islamic State attacks on Paris.

The post France after the Paris attacks: an interview with Olivier de France appeared first on European Geostrategy.