Proceedings of the 21st Conference on Artificial Intelligence (AAAI-06). Boston, MA, July 16–20, 2006. We consider the iterated belief change that occurs following an alternating sequence of actions and observations. At each instant, an agent has some beliefs about the action that occurs as well as beliefs about the resulting state of the world. We represent such problems by a sequence of ranking functions, so an agent assigns a quantitative plausibility value to every action and every state at each point in time. The resulting formalism is able to represent fallible knowledge, erroneous perception, exogenous actions, and failed actions. We illustrate that our framework is a generalization of several existing approaches to belief change, and it appropriately captures the non-elementary interaction between belief update and belief revision., Conference paper, Published.
We consider the iterated belief change that occurs following an alternating sequence of actions and observations. At each instant, an agent has beliefs about the actions that have occurred as well as beliefs about the resulting state of the world. We represent such problems by a sequence of ranking functions, so an agent assigns a quantitative plausibility value to every action and every state at each point in time. The resulting formalism is able to represent fallible belief, erroneous perception, exogenous actions, and failed actions. We illustrate that our framework is a generalization of several existing approaches to belief change, and it appropriately captures the non-elementary interaction between belief update and belief revision., Peer-reviewed article, Published.
Agents often try to convince others to hold certain beliefs. In fact, many network security attacks can actually be framed in terms of a dishonest that is trying to get an honest agent to believe some particular, untrue claims. While the study of belief change is an established area of research in Artificial Intelligence, there has been comparatively little exploration of the way one agent can explicitly manipulate the beliefs of another. In this paper, we introduce a precise, formal notion of a belief manipulation problem. We also illustrate that the meaning of a message can be parsed into different communicative acts, as defined in discourse analysis theory. Specifically, we suggest that each message can be understood in terms of what it says about the world, what it says about the message history, and what it says about future actions. We demonstrate that this kind of dissection can actually be used to discover the goals of an intruder in a communication session, which is important when determining how an adversary is trying to manipulate the beliefs of an honest agent. This information will then help prevent future attacks. We frame the discussion of belief manipulation primarily in the context of cryptographic protocol analysis., Peer-reviewed article, Published. Received: 17 January 2014; Accepted: 29 September 2014; Published: 10 October 2014.
Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence (IJCAI-17) in Melbourne, Australia 19-25 August 2017. Public announcements cause each agent in a group to modify their beliefs to incorporate some new piece of information, while simultaneously being aware that all other agents are doing the same. Given a set of agents and a set of epistemic goals, it is natural to ask if there is a single announcement that will make each agent believe the corresponding goal. This problem is known to be undecidable in a general modal setting, where the presence of nested beliefs can lead to complex dynamics. In this paper, we consider not necessarily truthful public announcements in the setting of AGM belief revision. We prove that announcement finding in this setting is not only decidable, but that it is simpler than the corresponding problem in the most simplified modal logics. We then describe an implemented tool that uses announcement finding to control robot behaviour through belief manipulation., Conference paper, Published.
Proceedings of the 15th International Workshop on Non-Monotonic Reasoning (NMR 2014), Vienna, Austria, 17–19 July 2014. Belief revision is the process in which an agent incorporates a new piece of information together with a pre-existing set of beliefs. When the new information comes in the form of a report from another agent, then it is clear that we must first determine whether or not that agent should be trusted. In this paper, we provide a formal approach to modeling trust as a pre-processing step before belief revision. We emphasize that trust is not simply a relation between agents; the trust that one agent has in another is often restricted to a particular domain of expertise. We demonstrate that this form of trust can be captured by associating a state-partition with each agent, then relativizing all reports to this state partition before performing belief revision. In this manner, we incorporate only the part of a report that falls under the perceived domain of expertise of the reporting agent. Unfortunately, state partitions based on expertise do not allow us to compare the relative strength of trust held with respect to different agents. To address this problem, we introduce pseudometrics over states to represent differing degrees of trust. This allows us to incorporate simultaneous reports from multiple agents in a way that ensures the most trusted reports will be believed., Conference paper, Published.
Providing appropriate prosthetic feet to those with limb loss is a complex and subjective process influenced by professional judgment and payer guidelines. This study used a small load cell (Europa™) at the base of the socket to measure the sagittal moments during walking with three objective categories of prosthetic feet in eleven individuals with transtibial limb loss with MFCL K2, K3 and K4 functional levels. Forefoot stiffness and hysteresis characteristics defined the three foot categories: Stiff, Intermediate, and Compliant. Prosthetic feet were randomly assigned and blinded from participants and investigators. After laboratory testing, participants completed one week community wear tests followed by a modified prosthetics evaluation questionnaire to determine if a specific category of prosthetic feet was preferred. The Compliant category of prosthetic feet was preferred by the participants (P=0.025) over the Stiff and Intermediate prosthetic feet, and the Compliant and Intermediate feet had 15% lower maximum sagittal moments during walking in the laboratory (P=0.0011) compared to the Stiff feet. The activity level of the participants did not change significantly with any of the wear tests in the community, suggesting that each foot was evaluated over a similar number of steps, but did not inherently increase activity. This is the first randomized double blind study in which prosthetic users have expressed a preference for a specific biomechanical characteristic of prosthetic feet: those with lower peak sagittal moments were preferred, and specifically preferred on slopes, stairs, uneven terrain, and during turns and maneuvering during real world use., Peer-reviewed article, Published.
Background: Bamboo is a highly abundant source of biomass which is underutilized despite having a chemical composition and fiber structure similar as wood. The main challenge for the industrial processing of bamboo is the high level of silica, which forms water-insoluble precipitates negetively affecting the process systems. A cost-competitive and eco-friendly scheme for the production of high-purity dissolving grade pulp from bamboo not only requires a process for silica removal, but also needs to fully utilize all of the materials dissolved in the process which includes lignin, and cellulosic and hemicellulosic sugars as well as the silica. Many investigations have been carried out to resolve the silica issue, but none of them has led to a commercial process. In this work, alkaline pretreatment of bamboo was conducted to extract silica prior to pulping process. The silica-free substrate was used to produce high-grade dissolving pulp. The dissolved silica, lignin, hemicellulosic sugars, and degraded cellulose in the spent liquors obtained from alkaline pretreatment and pulping process were recovered for providing high-value bio-based chemicals and fuel.
Results: An integrated process which combines dissolving pulp production with the recovery of excellent sustainable biofuel and biochemical feedstocks is presented in this work. Pretreatment at 95 °C with 12% NaOH charge for 150 min extracted all the silica and about 30% of the hemicellulose from bamboo. After kraft pulping, xylanase treatment and cold caustic extraction, pulp with hemicellulose content of about 3.5% was obtained. This pulp, after bleaching, provided a cellulose acetate grade dissolving pulp with α-cellulose content higher than 97% and hemicellulose content less than 2%. The amount of silica and lignin that could be recovered from the process corresponded to 95 and 77.86% of the two components in the original chips, respectively. Enzymatic hydrolysis and fermentation of the concentrated and detoxified sugar mixture liquor showed that an ethanol recovery of 0.46 g/g sugar was achieved with 93.2% of hydrolyzed sugars being consumed. A mass balance of the overall process showed that 76.59 g of solids was recovered from 100 g (o.d.) of green bamboo.
Conclusions: The present work proposes an integrated biorefinery process that contains alkaline pre-extraction, kraft pulping, enzyme treatment and cold caustic extraction for the production of high-grade dissolving pulp and recovery of silica, lignin, and hemicellulose from bamboo. This process could alleviate the silica-associated challenges and provide feedstocks for bio-based products, thereby allowing the improvement and expansion of bamboo utilization in industrial processes., Peer-reviewed article, Published. Received: 22 November 2016 ; Accepted: 2 February 2017 ; Published: 10 February 2017.
Proceedings of 2017 IEEE Conference on Communications and Network Security (CNS) in Las Vegas, NV, USA, USA, 9-11 Oct. 2017. We present an approach to tracking the behaviour of an attacker on a decoy system, where the decoy communicates with the real system only through low energy bluetooth. The result is a low-cost solution that does not interrupt the live system, while limiting potential damage. The attacker has no way to detect that they are being monitored, while their actions are being logged for further investigation. The system has been physically implemented using Raspberry PI and Arduino boards to replicate practical performance., Conference paper, Published.
The low-frequency asynchronous switch design (LF-ASD) was introduced as a direct brain-computer interface (BCI) technology for asynchronous control applications. The LF-ASD operates as an asynchronous brain switch (ABS) which is activated only when a user intends control and maintains an inactive state output when the user is not meaning to control the device (i.e., they may be idle, thinking about a problem, or performing some other action). Results from LF-ASD evaluations have shown promise, although the reported error rates are too high for most practical applications. This paper presents the evaluation of four new LF-ASD designs with data collected from individuals with high-level spinal cord injuries and able-bodied subjects. These new designs incorporated electroencephalographic energy normalization and feature space dimensionality reduction. The error characteristics of the new ABS designs were significantly better than the LF-ASD design with true positive rate increases of approximately 33% for false positive rates in the range of 1%-2%. The results demonstrate that the dimensionality of the LF-ASD feature space can be reduced without performance degradation. The results also confirm previous findings that spinal cord-injured subjects can operate ABS designs to the same ability as able-bodied subjects., Peer-reviewed article, Published. Manuscript received June 30, 2003; revised February 6, 2004.
The Neil Squire Society has developed asynchronous, direct brain switches for self-paced control applications with mean activation rates of 73% and false positive error rates of 2%. This report summarizes our results to date, lessons learned, and current directions, including research into implanted brain interface designs., Peer-reviewed article, Published. Manuscript received July 16, 2005; revised March 15, 2006; March 20, 2006.
Proceedings from Architectural Engineering Conference 2013, April 3-5, 2013 at State College, Pennsylvania, United States. Building performance is governed by physical processes, which are dynamically coupled in time and space, and whose degrees of interactions are often difficult to measure and appreciate. As a result, suboptimal performance and failures often occur. The goal of high-performance buildings is to optimize major aspects such as energy efficiency, life-cycle costs, and lighting, which are tightly coupled by the underlying physical processes. The premise behind this research project is that building integration/optimization can only be achieved when grounded on a shared understanding and communication of the underlying physical principles governing building performance, which can then enable the transformation of these principles into meaningful performance metrics. This paper proposes a methodology for building systems integration through building science principles. At the core of the methodology, a vocabulary of building science concepts, principles, and metrics enables using existing knowledge to increase understanding and gain insights on the systems involved in a particular design (including degrees of coupling, redundancies, and behaviours), which in turn facilitates the creation of new knowledge that may be needed to integrate new systems and technologies. A set of generic building science rules implemented using systems theory will enable such knowledge creation while preserving systems integrity at all times. The goal of this research is not to create a knowledge-base to replace building science professionals but to leverage an explicit vocabulary to increase understanding, learning, and communication of building performance for improved building integration. Furthermore, it is envisioned that the knowledge-base will serve as a bridge between building simulation, decision analysis, and optimization. This paper presents the initial attempt to organize a wealth of building science knowledge into a structured vocabulary. The power of generality and usability of the methodology will be tested with a case study. The expected benefits of the approach are three-fold: 1) to promote a more systematic approach to optimize building systems, 2) to facilitate the integration of new systems and technologies in buildings, and 3) to improve the education and dissemination of building science knowledge for improved building integration., Peer reviewed, Conference proceeding, Published.