Engineering Computational Emotion - A Reference Model for Emotion in Artificial Systems

Emotion is generally argued to be an influence on the behavior of life systems, largely concerning flexibility and adaptivity. The way in which life systems acts in response to a particular situations of the environment, has revealed the decisive and crucial importance of this feature in the success of behaviors. And this source of inspiration has influenced the way of thinking artificial systems. During the last decades, artificial systems have undergone such an evolution that each day more are integrated in our daily life. They have become greater in complexity, and the subsequent effects are related to an increased demand of systems that ensure resilience, robustness, availability, security or safety among others. All of them questions that raise quite a fundamental challenges in control design. This thesis has been developed under the framework of the Autonomous System project, a.k.a the ASys-Project. Short-term objectives of immediate application are focused on to design improved systems, and the approaching of intelligence in control strategies. Besides this, long-term objectives underlying ASys-Project concentrate on high order capabilities such as cognition, awareness and autonomy. This thesis is placed within the general fields of Engineery and Emotion science, and provides a theoretical foundation for engineering and designing computational emotion for artificial systems. The starting question that has grounded this thesis aims the problem of emotion--based autonomy. And how to feedback systems with valuable meaning has conformed the general objective. Both the starting question and the general objective, have underlaid the study of emotion, the influence on systems behavior, the key foundations that justify this feature in life systems, how emotion is integrated within the normal operation, and how this entire problem of emotion can be explained in artificial systems. By assuming essential differences concerning structure, purpose and operation between life and artificial systems, the essential motivation has been the exploration of what emotion solves in nature to afterwards analyze analogies for man--made systems. This work provides a reference model in which a collection of entities, relationships, models, functions and informational artifacts, are all interacting to provide the system with non-explicit knowledge under the form of emotion-like relevances. This solution aims to provide a reference model under which to design solutions for emotional operation, but related to the real needs of artificial systems. The proposal consists of a multi-purpose architecture that implement two broad modules in order to attend: (a) the range of processes related to the environment affectation, and (b) the range or processes related to the emotion perception-like and the higher levels of reasoning. This has required an intense and critical analysis beyond the state of the art around the most relevant theories of emotion and technical systems, in order to obtain the required support for those foundations that sustain each model. The problem has been interpreted and is described on the basis of AGSys, an agent assumed with the minimum rationality as to provide the capability to perform emotional assessment. AGSys is a conceptualization of a Model-based Cognitive agent that embodies an inner agent ESys, the responsible of performing the emotional operation inside of AGSys. The solution consists of multiple computational modules working federated, and aimed at conforming a mutual feedback loop between AGSys and ESys. Throughout this solution, the environment and the effects that might influence over the system are described as different problems. While AGSys operates as a common system within the external environment, ESys is designed to operate within a conceptualized inner environment. And this inner environment is built on the basis of those relevances that might occur inside of AGSys in the interaction with the external environment. This allows for a high-quality separate reasoning concerning mission goals defined in AGSys, and emotional goals defined in ESys. This way, it is provided a possible path for high-level reasoning under the influence of goals congruence. High-level reasoning model uses knowledge about emotional goals stability, letting this way new directions in which mission goals might be assessed under the situational state of this stability. This high-level reasoning is grounded by the work of MEP, a model of emotion perception that is thought as an analogy of a well-known theory in emotion science. The work of this model is described under the operation of a recursive-like process labeled as R-Loop, together with a system of emotional goals that are assumed as individual agents. This way, AGSys integrates knowledge that concerns the relation between a perceived object, and the effect which this perception induces on the situational state of the emotional goals. This knowledge enables a high-order system of information that provides the sustain for a high-level reasoning. The extent to which this reasoning might be approached is just delineated and assumed as future work. This thesis has been studied beyond a long range of fields of knowledge. This knowledge can be structured into two main objectives: (a) the fields of psychology, cognitive science, neurology and biological sciences in order to obtain understanding concerning the problem of the emotional phenomena, and (b) a large amount of computer science branches such as Autonomic Computing (AC), Self-adaptive software, Self-X systems, Model Integrated Computing (MIC) or the paradigm of models@runtime among others, in order to obtain knowledge about tools for designing each part of the solution. The final approach has been mainly performed on the basis of the entire acquired knowledge, and described under the fields of Artificial Intelligence, Model-Based Systems (MBS), and additional mathematical formalizations to provide punctual understanding in those cases that it has been required. This approach describes a reference model to feedback systems with valuable meaning, allowing for reasoning with regard to (a) the relationship between the environment and the relevance of the effects on the system, and (b) dynamical evaluations concerning the inner situational state of the system as a result of those effects. And this reasoning provides a framework of distinguishable states of AGSys derived from its own circumstances, that can be assumed as artificial emotion.

Common sense on chronic diseases, or, A rational treatise on the mechanical cause and cure of most chronic affections of the truncal organs of both male and female systems : embracing the author's views on physical education, and the present popular system of artificial life /

Included in the original collection of the Starling Medical College.

Knowledge based improvement:simulation and artificial intelligence for identifying and improving human decision-making in an operations systems

The performance of most operations systems is significantly affected by the interaction of human decision-makers. A methodology, based on the use of visual interactive simulation (VIS) and artificial intelligence (AI), is described that aims to identify and improve human decision-making in operations systems. The methodology, known as 'knowledge-based improvement' (KBI), elicits knowledge from a decision-maker via a VIS and then uses AI methods to represent decision-making. By linking the VIS and AI representation, it is possible to predict the performance of the operations system under different decision-making strategies and to search for improved strategies. The KBI methodology is applied to the decision-making surrounding unplanned maintenance operations at a Ford Motor Company engine assembly plant.

Administration routes affect the quality of immune responses:a cross-sectional evaluation of particulate antigen-delivery systems

Particulate delivery systems such as liposomes and polymeric nano- and microparticles are attracting great interest for developing new vaccines. Materials and formulation properties essential for this purpose have been extensively studied, but relatively little is known about the influence of the administration route of such delivery systems on the type and strength of immune response elicited. Thus, the present study aimed at elucidating the influence on the immune response when of immunising mice by different routes, such as the subcutaneous, intradermal, intramuscular, and intralymphatic routes with ovalbumin-loaded liposomes, N-trimethyl chitosan (TMC) nanoparticles, and poly(lactide-co-glycolide) (PLGA) microparticles, all with and without specifically selected immune-response modifiers. The results showed that the route of administration caused only minor differences in inducing an antibody response of the IgG1 subclass, and any such differences were abolished upon booster immunisation with the various adjuvanted and non-adjuvanted delivery systems. In contrast, the administration route strongly affected both the kinetics and magnitude of the IgG2a response. A single intralymphatic administration of all evaluated delivery systems induced a robust IgG2a response, whereas subcutaneous administration failed to elicit a substantial IgG2a response even after boosting, except with the adjuvanted nanoparticles. The intradermal and intramuscular routes generated intermediate IgG2a titers. The benefit of the intralymphatic administration route for eliciting a Th1-type response was confirmed in terms of IFN-gamma production of isolated and re-stimulated splenocytes from animals previously immunised with adjuvanted and non-adjuvanted liposomes as well as with adjuvanted microparticles. Altogether the results show that the IgG2a associated with Th1-type immune responses are sensitive to the route of administration, whereas IgG1 response associated with Th2-type immune responses were relatively insensitive to the administration route of the particulate delivery systems. The route of administration should therefore be considered when planning and interpreting pre-clinical research or development on vaccine delivery systems.

Effect of incorporating cholesterol into DDA:TDB liposomal adjuvants on Bilayer properties, biodistribution, and immune responses

Cholesterol is an abundant component of mammalian cell membranes and has been extensively studied as an artificial membrane stabilizer in a wide range of phospholipid liposome systems. In this study, the aim was to investigate the role of cholesterol in cationic liposomal adjuvant system based on dimethyldioctadecylammonium (DDA) and trehalose 6,6'-dibehenate (TDB) which has been shown as a strong adjuvant system for vaccines against a wide range of diseases. Packaging of cholesterol within DDA:TDB liposomes was investigated using differential scanning calorimetery and surface pressure-area isotherms of lipid monolayers; incorporation of cholesterol into liposomal membranes promoted the formation of a liquid-condensed monolayer and removed the main phase transition temperature of the system, resulting in an increased bilayer fluidity and reduced antigen retention in vitro. In vivo biodistribution studies found that this increase in membrane fluidity did not alter deposition of liposomes and antigen at the site of injection. In terms of immune responses, early (12 days after immunization) IgG responses were reduced by inclusion of cholesterol; thereafter there were no differences in antibody (IgG, IgG1, IgG2b) responses promoted by DDA:TDB liposomes with and without cholesterol. However, significantly higher levels of IFN-gamma were induced by DDA:TDB liposomes, and liposome uptake by macrophages in vitro was also shown to be higher for DDA:TDB liposomes compared to their cholesterol-containing counterparts, suggesting that small changes in bilayer mechanics can impact both cellular interactions and immune responses. © 2013 American Chemical Society.

Effect of incorporating cholesterol into DDA:TDB liposomal adjuvants on Bilayer properties, biodistribution, and immune responses

Cholesterol is an abundant component of mammalian cell membranes and has been extensively studied as an artificial membrane stabilizer in a wide range of phospholipid liposome systems. In this study, the aim was to investigate the role of cholesterol in cationic liposomal adjuvant system based on dimethyldioctadecylammonium (DDA) and trehalose 6,6'-dibehenate (TDB) which has been shown as a strong adjuvant system for vaccines against a wide range of diseases. Packaging of cholesterol within DDA:TDB liposomes was investigated using differential scanning calorimetery and surface pressure-area isotherms of lipid monolayers; incorporation of cholesterol into liposomal membranes promoted the formation of a liquid-condensed monolayer and removed the main phase transition temperature of the system, resulting in an increased bilayer fluidity and reduced antigen retention in vitro. In vivo biodistribution studies found that this increase in membrane fluidity did not alter deposition of liposomes and antigen at the site of injection. In terms of immune responses, early (12 days after immunization) IgG responses were reduced by inclusion of cholesterol; thereafter there were no differences in antibody (IgG, IgG1, IgG2b) responses promoted by DDA:TDB liposomes with and without cholesterol. However, significantly higher levels of IFN-gamma were induced by DDA:TDB liposomes, and liposome uptake by macrophages in vitro was also shown to be higher for DDA:TDB liposomes compared to their cholesterol-containing counterparts, suggesting that small changes in bilayer mechanics can impact both cellular interactions and immune responses. © 2013 American Chemical Society.

An immune inspired Network Intrusion Detection System utilising correlation

Network Intrusion Detection Systems (NIDS) are computer systems which monitor a network with the aim of discerning malicious from benign activity on that network. While a wide range of approaches have met varying levels of success, most IDSs rely on having access to a database of known attack signatures which are written by security experts. Nowadays, in order to solve problems with false positive alerts, correlation algorithms are used to add additional structure to sequences of IDS alerts. However, such techniques are of no help in discovering novel attacks or variations of known attacks, something the human immune system (HIS) is capable of doing in its own specialised domain. This paper presents a novel immune algorithm for application to the IDS problem. The goal is to discover packets containing novel variations of attacks covered by an existing signature base.