@inproceedings{3337,
abstract = {Playing table tennis is a difficult task for robots, especially due to their limitations of acceleration. A key bottleneck is the amount of time needed to reach the desired hitting position and velocity of the racket for returning the incoming ball. Here, it often does not suffice to simply extrapolate the ball's trajectory after the opponent returns it but more information is needed. Humans are able to predict the ball's trajectory based on the opponent's moves and, thus, have a considerable advantage. Hence, we propose to incorporate an anticipation system into robot table tennis players, which enables the robot to react earlier while the opponent is performing the striking movement. Based on visual observation of the opponent's racket movement, the robot can predict the aim of the opponent and adjust its movement generation accordingly. The policies for deciding how and when to react are obtained by reinforcement learning. We conduct experiments with an existing robot player to show that the learned reaction policy can significantly improve the performance of the overall system.},
author = {Wang, Zhikun and Lampert, Christoph and Mülling, Katharina and Schölkopf, Bernhard and Peters, Jan},
location = {San Francisco, USA},
pages = {332 -- 337},
publisher = {IEEE},
title = {{Learning anticipation policies for robot table tennis}},
doi = {10.1109/IROS.2011.6094892},
year = {2011},
}
@inproceedings{3163,
abstract = {We study multi-label prediction for structured output sets, a problem that occurs, for example, in object detection in images, secondary structure prediction in computational biology, and graph matching with symmetries. Conventional multilabel classification techniques are typically not applicable in this situation, because they require explicit enumeration of the label set, which is infeasible in case of structured outputs. Relying on techniques originally designed for single-label structured prediction, in particular structured support vector machines, results in reduced prediction accuracy, or leads to infeasible optimization problems. In this work we derive a maximum-margin training formulation for multi-label structured prediction that remains computationally tractable while achieving high prediction accuracy. It also shares most beneficial properties with single-label maximum-margin approaches, in particular formulation as a convex optimization problem, efficient working set training, and PAC-Bayesian generalization bounds.},
author = {Lampert, Christoph},
location = {Granada, Spain},
publisher = {Neural Information Processing Systems},
title = {{Maximum margin multi-label structured prediction}},
year = {2011},
}
@misc{3322,
abstract = {We study multi-label prediction for structured output spaces, a problem that occurs, for example, in object detection in images, secondary structure prediction in computational biology, and graph matching with symmetries. Conventional multi-label classification techniques are typically not applicable in this situation, because they require explicit enumeration of the label space, which is infeasible in case of structured outputs. Relying on techniques originally designed for single- label structured prediction, in particular structured support vector machines, results in reduced prediction accuracy, or leads to infeasible optimization problems. In this work we derive a maximum-margin training formulation for multi-label structured prediction that remains computationally tractable while achieving high prediction accuracy. It also shares most beneficial properties with single-label maximum-margin approaches, in particular a formulation as a convex optimization problem, efficient working set training, and PAC-Bayesian generalization bounds.},
author = {Lampert, Christoph},
booktitle = {NIPS: Neural Information Processing Systems},
publisher = {Neural Information Processing Systems},
title = {{Maximum margin multi label structured prediction}},
year = {2011},
}
@inproceedings{3346,
abstract = {We study Markov decision processes (MDPs) with multiple limit-average (or mean-payoff) functions. We consider two different objectives, namely, expectation and satisfaction objectives. Given an MDP with k reward functions, in the expectation objective the goal is to maximize the expected limit-average value, and in the satisfaction objective the goal is to maximize the probability of runs such that the limit-average value stays above a given vector. We show that under the expectation objective, in contrast to the single-objective case, both randomization and memory are necessary for strategies, and that finite-memory randomized strategies are sufficient. Under the satisfaction objective, in contrast to the single-objective case, infinite memory is necessary for strategies, and that randomized memoryless strategies are sufficient for epsilon-approximation, for all epsilon>;0. We further prove that the decision problems for both expectation and satisfaction objectives can be solved in polynomial time and the trade-off curve (Pareto curve) can be epsilon-approximated in time polynomial in the size of the MDP and 1/epsilon, and exponential in the number of reward functions, for all epsilon>;0. Our results also reveal flaws in previous work for MDPs with multiple mean-payoff functions under the expectation objective, correct the flaws and obtain improved results.},
author = {Brázdil, Tomáš and Brožek, Václav and Chatterjee, Krishnendu and Forejt, Vojtěch and Kučera, Antonín},
location = {Toronto, Canada},
publisher = {IEEE},
title = {{Two views on multiple mean payoff objectives in Markov Decision Processes}},
doi = {10.1109/LICS.2011.10},
year = {2011},
}
@inproceedings{3347,
abstract = {The class of omega-regular languages provides a robust specification language in verification. Every omega-regular condition can be decomposed into a safety part and a liveness part. The liveness part ensures that something good happens "eventually". Finitary liveness was proposed by Alur and Henzinger as a stronger formulation of liveness. It requires that there exists an unknown, fixed bound b such that something good happens within b transitions. In this work we consider automata with finitary acceptance conditions defined by finitary Buchi, parity and Streett languages. We study languages expressible by such automata: we give their topological complexity and present a regular-expression characterization. We compare the expressive power of finitary automata and give optimal algorithms for classical decisions questions. We show that the finitary languages are Sigma 2-complete; we present a complete picture of the expressive power of various classes of automata with finitary and infinitary acceptance conditions; we show that the languages defined by finitary parity automata exactly characterize the star-free fragment of omega B-regular languages; and we show that emptiness is NLOGSPACE-complete and universality as well as language inclusion are PSPACE-complete for finitary parity and Streett automata.},
author = {Chatterjee, Krishnendu and Fijalkow, Nathanaël},
location = {Tarragona, Spain},
pages = {216 -- 226},
publisher = {Springer},
title = {{Finitary languages}},
doi = {10.1007/978-3-642-21254-3_16},
volume = {6638},
year = {2011},
}
@inproceedings{3348,
abstract = {We study synthesis of controllers for real-time systems, where the objective is to stay in a given safe set. The problem is solved by obtaining winning strategies in the setting of concurrent two-player timed automaton games with safety objectives. To prevent a player from winning by blocking time, we restrict each player to strategies that ensure that the player cannot be responsible for causing a zeno run. We construct winning strategies for the controller which require access only to (1) the system clocks (thus, controllers which require their own internal infinitely precise clocks are not necessary), and (2) a linear (in the number of clocks) number of memory bits. Precisely, we show that for safety objectives, a memory of size (3 · |C|+lg(|C|+1)) bits suffices for winning controller strategies, where C is the set of clocks of the timed automaton game, significantly improving the previous known exponential bound. We also settle the open question of whether winning region controller strategies require memory for safety objectives by showing with an example the necessity of memory for region strategies to win for safety objectives.},
author = {Chatterjee, Krishnendu and Prabhu, Vinayak},
location = {Chicago, USA},
pages = {221 -- 230},
publisher = {Springer},
title = {{Synthesis of memory efficient real time controllers for safety objectives}},
doi = {10.1145/1967701.1967734},
year = {2011},
}
@inproceedings{3349,
abstract = {Games on graphs provide a natural model for reactive non-terminating systems. In such games, the interaction of two players on an arena results in an infinite path that describes a run of the system. Different settings are used to model various open systems in computer science, as for instance turn-based or concurrent moves, and deterministic or stochastic transitions. In this paper, we are interested in turn-based games, and specifically in deterministic parity games and stochastic reachability games (also known as simple stochastic games). We present a simple, direct and efficient reduction from deterministic parity games to simple stochastic games: it yields an arena whose size is linear up to a logarithmic factor in size of the original arena.},
author = {Chatterjee, Krishnendu and Fijalkow, Nathanaël},
location = {Minori, Italy},
pages = {74 -- 86},
publisher = {EPTCS},
title = {{A reduction from parity games to simple stochastic games}},
doi = {10.4204/EPTCS.54.6},
volume = {54},
year = {2011},
}
@inproceedings{3350,
abstract = {A controller for a discrete game with ω-regular objectives requires attention if, intuitively, it requires measuring the state and switching from the current control action. Minimum attention controllers are preferable in modern shared implementations of cyber-physical systems because they produce the least burden on system resources such as processor time or communication bandwidth. We give algorithms to compute minimum attention controllers for ω-regular objectives in imperfect information discrete two-player games. We show a polynomial-time reduction from minimum attention controller synthesis to synthesis of controllers for mean-payoff parity objectives in games of incomplete information. This gives an optimal EXPTIME-complete synthesis algorithm. We show that the minimum attention controller problem is decidable for infinite state systems with finite bisimulation quotients. In particular, the problem is decidable for timed and rectangular automata.},
author = {Chatterjee, Krishnendu and Majumdar, Ritankar},
editor = {Fahrenberg, Uli and Tripakis, Stavros},
location = {Aalborg, Denmark},
pages = {145 -- 159},
publisher = {Springer},
title = {{Minimum attention controller synthesis for omega regular objectives}},
doi = {10.1007/978-3-642-24310-3_11},
volume = {6919},
year = {2011},
}
@inproceedings{3351,
abstract = {In two-player games on graph, the players construct an infinite path through the game graph and get a reward computed by a payoff function over infinite paths. Over weighted graphs, the typical and most studied payoff functions compute the limit-average or the discounted sum of the rewards along the path. Besides their simple definition, these two payoff functions enjoy the property that memoryless optimal strategies always exist. In an attempt to construct other simple payoff functions, we define a class of payoff functions which compute an (infinite) weighted average of the rewards. This new class contains both the limit-average and the discounted sum functions, and we show that they are the only members of this class which induce memoryless optimal strategies, showing that there is essentially no other simple payoff functions.},
author = {Chatterjee, Krishnendu and Doyen, Laurent and Singh, Rohit},
editor = {Owe, Olaf and Steffen, Martin and Telle, Jan Arne},
location = {Oslo, Norway},
pages = {148 -- 159},
publisher = {Springer},
title = {{On memoryless quantitative objectives}},
doi = {10.1007/978-3-642-22953-4_13},
volume = {6914},
year = {2011},
}
@article{3352,
abstract = {Exploring the connection of biology with reactive systems to better understand living systems.},
author = {Fisher, Jasmin and Harel, David and Henzinger, Thomas A},
journal = {Communications of the ACM},
number = {10},
pages = {72 -- 82},
publisher = {ACM},
title = {{Biology as reactivity}},
doi = {10.1145/2001269.2001289},
volume = {54},
year = {2011},
}
@article{3354,
abstract = {We consider two-player games played on a finite state space for an infinite number of rounds. The games are concurrent: in each round, the two players (player 1 and player 2) choose their moves independently and simultaneously; the current state and the two moves determine the successor state. We consider ω-regular winning conditions specified as parity objectives. Both players are allowed to use randomization when choosing their moves. We study the computation of the limit-winning set of states, consisting of the states where the sup-inf value of the game for player 1 is 1: in other words, a state is limit-winning if player 1 can ensure a probability of winning arbitrarily close to 1. We show that the limit-winning set can be computed in O(n2d+2) time, where n is the size of the game structure and 2d is the number of priorities (or colors). The membership problem of whether a state belongs to the limit-winning set can be decided in NP ∩ coNP. While this complexity is the same as for the simpler class of turn-based parity games, where in each state only one of the two players has a choice of moves, our algorithms are considerably more involved than those for turn-based games. This is because concurrent games do not satisfy two of the most fundamental properties of turn-based parity games. First, in concurrent games limit-winning strategies require randomization; and second, they require infinite memory.},
author = {Chatterjee, Krishnendu and De Alfaro, Luca and Henzinger, Thomas A},
journal = {ACM Transactions on Computational Logic (TOCL)},
number = {4},
publisher = {ACM},
title = {{Qualitative concurrent parity games}},
doi = {10.1145/1970398.1970404},
volume = {12},
year = {2011},
}
@unpublished{3339,
abstract = {Turn-based stochastic games and its important subclass Markov decision processes (MDPs) provide models for systems with both probabilistic and nondeterministic behaviors. We consider turn-based stochastic games with two classical quantitative objectives: discounted-sum and long-run average objectives. The game models and the quantitative objectives are widely used in probabilistic verification, planning, optimal inventory control, network protocol and performance analysis. Games and MDPs that model realistic systems often have very large state spaces, and probabilistic abstraction techniques are necessary to handle the state-space explosion. The commonly used full-abstraction techniques do not yield space-savings for systems that have many states with similar value, but does not necessarily have similar transition structure. A semi-abstraction technique, namely Magnifying-lens abstractions (MLA), that clusters states based on value only, disregarding differences in their transition relation was proposed for qualitative objectives (reachability and safety objectives). In this paper we extend the MLA technique to solve stochastic games with discounted-sum and long-run average objectives. We present the MLA technique based abstraction-refinement algorithm for stochastic games and MDPs with discounted-sum objectives. For long-run average objectives, our solution works for all MDPs and a sub-class of stochastic games where every state has the same value. },
author = {Chatterjee, Krishnendu and De Alfaro, Luca and Pritam, Roy},
booktitle = {arXiv},
pages = {17},
publisher = {ArXiv},
title = {{Magnifying lens abstraction for stochastic games with discounted and long-run average objectives}},
year = {2011},
}
@inproceedings{3342,
abstract = {We consider Markov decision processes (MDPs) with ω-regular specifications given as parity objectives. We consider the problem of computing the set of almost-sure winning states from where the objective can be ensured with probability 1. The algorithms for the computation of the almost-sure winning set for parity objectives iteratively use the solutions for the almost-sure winning set for Büchi objectives (a special case of parity objectives). Our contributions are as follows: First, we present the first subquadratic symbolic algorithm to compute the almost-sure winning set for MDPs with Büchi objectives; our algorithm takes O(nm) symbolic steps as compared to the previous known algorithm that takes O(n 2) symbolic steps, where n is the number of states and m is the number of edges of the MDP. In practice MDPs often have constant out-degree, and then our symbolic algorithm takes O(nn) symbolic steps, as compared to the previous known O(n 2) symbolic steps algorithm. Second, we present a new algorithm, namely win-lose algorithm, with the following two properties: (a) the algorithm iteratively computes subsets of the almost-sure winning set and its complement, as compared to all previous algorithms that discover the almost-sure winning set upon termination; and (b) requires O(nK) symbolic steps, where K is the maximal number of edges of strongly connected components (scc’s) of the MDP. The win-lose algorithm requires symbolic computation of scc’s. Third, we improve the algorithm for symbolic scc computation; the previous known algorithm takes linear symbolic steps, and our new algorithm improves the constants associated with the linear number of steps. In the worst case the previous known algorithm takes 5·n symbolic steps, whereas our new algorithm takes 4 ·n symbolic steps.},
author = {Chatterjee, Krishnendu and Henzinger, Monika and Joglekar, Manas and Nisarg, Shah},
editor = {Gopalakrishnan, Ganesh and Qadeer, Shaz},
location = {Snowbird, USA},
pages = {260 -- 276},
publisher = {Springer},
title = {{Symbolic algorithms for qualitative analysis of Markov decision processes with Büchi objectives}},
doi = {10.1007/978-3-642-22110-1_21},
volume = {6806},
year = {2011},
}
@inproceedings{3343,
abstract = {We present faster and dynamic algorithms for the following problems arising in probabilistic verification: Computation of the maximal end-component (mec) decomposition of Markov decision processes (MDPs), and of the almost sure winning set for reachability and parity objectives in MDPs. We achieve the following running time for static algorithms in MDPs with graphs of n vertices and m edges: (1) O(m · min{ √m, n2/3 }) for the mec decomposition, improving the longstanding O(m·n) bound; (2) O(m·n2/3) for reachability objectives, improving the previous O(m · √m) bound for m > n4/3; and (3) O(m · min{ √m, n2/3 } · log(d)) for parity objectives with d priorities, improving the previous O(m · √m · d) bound. We also give incremental and decremental algorithms in linear time for mec decomposition and reachability objectives and O(m · log d) time for parity ob jectives.},
author = {Chatterjee, Krishnendu and Henzinger, Monika},
location = {San Francisco, USA},
pages = {1318 -- 1336},
publisher = {SIAM},
title = {{Faster and dynamic algorithms for maximal end component decomposition and related graph problems in probabilistic verification}},
doi = {10.1137/1.9781611973082.101},
year = {2011},
}
@inproceedings{3344,
abstract = {Games played on graphs provide the mathematical framework to analyze several important problems in computer science as well as mathematics, such as the synthesis problem of Church, model checking of open reactive systems and many others. On the basis of mode of interaction of the players these games can be classified as follows: (a) turn-based (players make moves in turns); and (b) concurrent (players make moves simultaneously). On the basis of the information available to the players these games can be classified as follows: (a) perfect-information (players have perfect view of the game); and (b) partial-information (players have partial view of the game). In this talk we will consider all these classes of games with reachability objectives, where the goal of one player is to reach a set of target vertices of the graph, and the goal of the opponent player is to prevent the player from reaching the target. We will survey the results for various classes of games, and the results range from linear time decision algorithms to EXPTIME-complete problems to undecidable problems.},
author = {Chatterjee, Krishnendu},
editor = {Delzanno, Giorgo and Potapov, Igor},
location = {Genoa, Italy},
pages = {1 -- 1},
publisher = {Springer},
title = {{Graph games with reachability objectives}},
doi = {10.1007/978-3-642-24288-5_1},
volume = {6945},
year = {2011},
}
@inproceedings{3367,
abstract = {In this paper, we present the first output-sensitive algorithm to compute the persistence diagram of a filtered simplicial complex. For any Γ>0, it returns only those homology classes with persistence at least Γ. Instead of the classical reduction via column operations, our algorithm performs rank computations on submatrices of the boundary matrix. For an arbitrary constant δ ∈ (0,1), the running time is O(C(1-δ)ΓR(n)log n), where C(1-δ)Γ is the number of homology classes with persistence at least (1-δ)Γ, n is the total number of simplices, and R(n) is the complexity of computing the rank of an n x n matrix with O(n) nonzero entries. Depending on the choice of the rank algorithm, this yields a deterministic O(C(1-δ)Γn2.376) algorithm, a O(C(1-δ)Γn2.28) Las-Vegas algorithm, or a O(C(1-δ)Γn2+ε) Monte-Carlo algorithm for an arbitrary ε>0.},
author = {Chen, Chao and Kerber, Michael},
location = {Paris, France},
pages = {207 -- 216},
publisher = {ACM},
title = {{An output sensitive algorithm for persistent homology}},
doi = {10.1145/1998196.1998228},
year = {2011},
}
@article{3368,
abstract = {Tissue surface tension (TST) is an important mechanical property influencing cell sorting and tissue envelopment. The study by Manning et al. (1) reported on a mathematical model describing TST on the basis of the balance between adhesive and tensile properties of the constituent cells. The model predicts that, in high-adhesion cell aggregates, surface cells will be stretched to maintain the same area of cell–cell contact as interior bulk cells, resulting in an elongated and flattened cell shape. The authors (1) observed flat and elongated cells at the surface of high-adhesion zebrafish germ-layer explants, which they argue are undifferentiated stretched germ-layer progenitor cells, and they use this observation as a validation of their model.},
author = {Krens, Gabriel and Möllmert, Stephanie and Heisenberg, Carl-Philipp J},
journal = {PNAS},
number = {3},
pages = {E9 -- E10},
publisher = {National Academy of Sciences},
title = {{Enveloping cell layer differentiation at the surface of zebrafish germ layer tissue explants}},
doi = {10.1073/pnas.1010767108},
volume = {108},
year = {2011},
}
@article{3369,
abstract = {Rab3 interacting molecules (RIMs) are highly enriched in the active zones of presynaptic terminals. It is generally thought that they operate as effectors of the small G protein Rab3. Three recent papers, by Han et al. (this issue of Neuron), Deng et al. (this issue of Neuron), and Kaeser et al. (a recent issue of Cell), shed new light on the functional role of RIM in presynaptic terminals. First, RIM tethers Ca2+ channels to active zones. Second, RIM contributes to priming of synaptic vesicles by interacting with another presynaptic protein, Munc13.},
author = {Pernia-Andrade, Alejandro and Jonas, Peter M},
journal = {Neuron},
number = {2},
pages = {185 -- 187},
publisher = {Elsevier},
title = {{The multiple faces of RIM}},
doi = {10.1016/j.neuron.2011.01.010},
volume = {69},
year = {2011},
}
@article{3370,
abstract = {Supertree methods are widely applied and give rise to new conclusions about phylogenies (e.g., Bininda-Emonds et al. 2007). Although several desiderata for supertree methods exist (Wilkinson, Thorley, et al. 2004), only few of them have been studied in greater detail, examples include shape bias (Wilkinson et al. 2005) or pareto properties (Wilkinson et al. 2007). Here I look more closely at two matrix representation methods, matrix representation with compatibility (MRC) and matrix representation with parsimony (MRP). Different null models of random data are studied and the resulting tree shapes are investigated. Thereby I consider unrooted trees and a bias in tree shape is determined by a tree balance measure. The measure for unrooted trees is a modification of a tree balance measure for rooted trees. I observe that depending on the underlying null model of random data, the methods may resolve conflict in favor of more balanced tree shapes. The analyses refer only to trees with the same taxon set, also known as the consensus setting (e.g., Wilkinson et al. 2007), but I will be able to draw conclusions on how to deal with missing data.},
author = {Kupczok, Anne},
journal = {Systematic Biology},
number = {2},
pages = {218 -- 225},
publisher = {Oxford University Press},
title = {{Consequences of different null models on the tree shape bias of supertree methods}},
doi = {10.1093/sysbio/syq086},
volume = {60},
year = {2011},
}
@article{3372,
abstract = {Nowak et al.1 argue that inclusive fitness theory has been of little value in explaining the natural world, and that it has led to negligible progress in explaining the evolution of eusociality. However, we believe that their arguments are based upon a misunderstanding of evolutionary theory and a misrepresentation of the empirical literature. We will focus our comments on three general issues.},
author = {Abbot, Patrick and Abe, Jun and Alcock, John and Alizon, Samuel and Alpedrinha, Joao and Andersson, Malte and Andre, Jean and Van Baalen, Minus and Balloux, Francois and Balshine, Sigal and Barton, Nicholas H and Beukeboom, Leo and Biernaskie, Jay and Bilde, Trine and Borgia, Gerald and Breed, Michael and Brown, Sam and Bshary, Redouan and Buckling, Angus and Burley, Nancy and Burton Chellew, Max and Cant, Michael and Chapuisat, Michel and Charnov, Eric and Clutton Brock, Tim and Cockburn, Andrew and Cole, Blaine and Colegrave, Nick and Cosmides, Leda and Couzin, Iain and Coyne, Jerry and Creel, Scott and Crespi, Bernard and Curry, Robert and Dall, Sasha and Day, Troy and Dickinson, Janis and Dugatkin, Lee and El Mouden, Claire and Emlen, Stephen and Evans, Jay and Ferriere, Regis and Field, Jeremy and Foitzik, Susanne and Foster, Kevin and Foster, William and Fox, Charles and Gadau, Juergen and Gandon, Sylvain and Gardner, Andy and Gardner, Michael and Getty, Thomas and Goodisman, Michael and Grafen, Alan and Grosberg, Rick and Grozinger, Christina and Gouyon, Pierre and Gwynne, Darryl and Harvey, Paul and Hatchwell, Ben and Heinze, Jürgen and Helantera, Heikki and Helms, Ken and Hill, Kim and Jiricny, Natalie and Johnstone, Rufus and Kacelnik, Alex and Kiers, E Toby and Kokko, Hanna and Komdeur, Jan and Korb, Judith and Kronauer, Daniel and Kümmerli, Rolf and Lehmann, Laurent and Linksvayer, Timothy and Lion, Sébastien and Lyon, Bruce and Marshall, James and Mcelreath, Richard and Michalakis, Yannis and Michod, Richard and Mock, Douglas and Monnin, Thibaud and Montgomerie, Robert and Moore, Allen and Mueller, Ulrich and Noë, Ronald and Okasha, Samir and Pamilo, Pekka and Parker, Geoff and Pedersen, Jes and Pen, Ido and Pfennig, David and Queller, David and Rankin, Daniel and Reece, Sarah and Reeve, Hudson and Reuter, Max and Roberts, Gilbert and Robson, Simon and Roze, Denis and Rousset, Francois and Rueppell, Olav and Sachs, Joel and Santorelli, Lorenzo and Schmid Hempel, Paul and Schwarz, Michael and Scott Phillips, Tom and Shellmann Sherman, Janet and Sherman, Paul and Shuker, David and Smith, Jeff and Spagna, Joseph and Strassmann, Beverly and Suarez, Andrew and Sundström, Liselotte and Taborsky, Michael and Taylor, Peter and Thompson, Graham and Tooby, John and Tsutsui, Neil and Tsuji, Kazuki and Turillazzi, Stefano and Úbeda, Francisco and Vargo, Edward and Voelkl, Bernard and Wenseleers, Tom and West, Stuart and West Eberhard, Mary and Westneat, David and Wiernasz, Diane and Wild, Geoff and Wrangham, Richard and Young, Andrew and Zeh, David and Zeh, Jeanne and Zink, Andrew},
journal = {Nature},
number = {7339},
pages = {E1 -- E4},
publisher = {Nature Publishing Group},
title = {{Inclusive fitness theory and eusociality}},
doi = {10.1038/nature09831},
volume = {471},
year = {2011},
}